[ML] DF Analytics Classification exploration: replace table with data grid (#63757)
* update classification result to use datagrid * consider isTraining in docCount fetch * fix translations
This commit is contained in:
Melissa Alvarez
GitHub
parent
32c6fd777f
commit
784b8beb2f
8 changed files with 421 additions and 514 deletions
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@ -52,7 +52,7 @@ export interface ClassificationAnalysis {
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classification: Classification;
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}
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export interface LoadRegressionExploreDataArg {
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export interface LoadExploreDataArg {
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filterByIsTraining?: boolean;
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searchQuery: SavedSearchQuery;
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}
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@ -409,11 +409,11 @@ export function getEvalQueryBody({
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ignoreDefaultQuery,
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}: {
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resultsField: string;
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isTraining: boolean;
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isTraining?: boolean;
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searchQuery?: ResultsSearchQuery;
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ignoreDefaultQuery?: boolean;
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}) {
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let query;
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let query: any;
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const trainingQuery: ResultsSearchQuery = {
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term: { [`${resultsField}.is_training`]: { value: isTraining } },
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@ -426,19 +426,25 @@ export function getEvalQueryBody({
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searchQueryClone.bool.must = [];
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}
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searchQueryClone.bool.must.push(trainingQuery);
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if (isTraining !== undefined) {
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searchQueryClone.bool.must.push(trainingQuery);
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}
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query = searchQueryClone;
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} else if (isQueryStringQuery(searchQueryClone)) {
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query = {
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bool: {
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must: [searchQueryClone, trainingQuery],
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must: [searchQueryClone],
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},
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};
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if (isTraining !== undefined) {
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query.bool.must.push(trainingQuery);
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}
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} else {
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// Not a bool or string query so we need to create it so can add the trainingQuery
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query = {
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bool: {
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must: [trainingQuery],
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must: isTraining !== undefined ? [trainingQuery] : [],
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},
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};
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}
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@ -456,7 +462,7 @@ interface EvaluateMetrics {
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}
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interface LoadEvalDataConfig {
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isTraining: boolean;
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isTraining?: boolean;
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index: string;
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dependentVariable: string;
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resultsField: string;
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@ -535,7 +541,7 @@ interface TrackTotalHitsSearchResponse {
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interface LoadDocsCountConfig {
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ignoreDefaultQuery?: boolean;
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isTraining: boolean;
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isTraining?: boolean;
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searchQuery: SavedSearchQuery;
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resultsField: string;
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destIndex: string;
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@ -0,0 +1,135 @@
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/*
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* Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
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* or more contributor license agreements. Licensed under the Elastic License;
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* you may not use this file except in compliance with the Elastic License.
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*/
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import React, { Dispatch, FC, SetStateAction, useCallback, useMemo } from 'react';
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import { i18n } from '@kbn/i18n';
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import { EuiDataGrid, EuiDataGridPaginationProps, EuiDataGridSorting } from '@elastic/eui';
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import { euiDataGridStyle, euiDataGridToolbarSettings } from '../../../../common';
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import { mlFieldFormatService } from '../../../../../services/field_format_service';
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import { IndexPattern } from '../../../../../../../../../../src/plugins/data/public';
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const PAGE_SIZE_OPTIONS = [5, 10, 25, 50];
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type Pagination = Pick<EuiDataGridPaginationProps, 'pageIndex' | 'pageSize'>;
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type TableItem = Record<string, any>;
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interface ExplorationDataGridProps {
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colorRange?: (d: number) => string;
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columns: any[];
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indexPattern: IndexPattern;
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pagination: Pagination;
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resultsField: string;
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rowCount: number;
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selectedFields: string[];
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setPagination: Dispatch<SetStateAction<Pagination>>;
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setSelectedFields: Dispatch<SetStateAction<string[]>>;
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setSortingColumns: Dispatch<SetStateAction<EuiDataGridSorting['columns']>>;
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sortingColumns: EuiDataGridSorting['columns'];
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tableItems: TableItem[];
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}
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export const ClassificationExplorationDataGrid: FC<ExplorationDataGridProps> = ({
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columns,
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indexPattern,
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pagination,
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resultsField,
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rowCount,
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selectedFields,
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setPagination,
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setSelectedFields,
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setSortingColumns,
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sortingColumns,
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tableItems,
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}) => {
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const renderCellValue = useMemo(() => {
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return ({ rowIndex, columnId }: { rowIndex: number; columnId: string; setCellProps: any }) => {
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const adjustedRowIndex = rowIndex - pagination.pageIndex * pagination.pageSize;
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const fullItem = tableItems[adjustedRowIndex];
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if (fullItem === undefined) {
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return null;
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}
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let format: any;
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if (indexPattern !== undefined) {
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format = mlFieldFormatService.getFieldFormatFromIndexPattern(indexPattern, columnId, '');
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}
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const cellValue =
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fullItem.hasOwnProperty(columnId) && fullItem[columnId] !== undefined
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? fullItem[columnId]
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: null;
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if (format !== undefined) {
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return format.convert(cellValue, 'text');
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}
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if (typeof cellValue === 'string' || cellValue === null) {
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return cellValue;
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}
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if (typeof cellValue === 'boolean') {
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return cellValue ? 'true' : 'false';
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}
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if (typeof cellValue === 'object' && cellValue !== null) {
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return JSON.stringify(cellValue);
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}
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return cellValue;
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};
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}, [resultsField, rowCount, tableItems, pagination.pageIndex, pagination.pageSize]);
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const onChangeItemsPerPage = useCallback(
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pageSize => {
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setPagination(p => {
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const pageIndex = Math.floor((p.pageSize * p.pageIndex) / pageSize);
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return { pageIndex, pageSize };
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});
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},
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[setPagination]
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);
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const onChangePage = useCallback(pageIndex => setPagination(p => ({ ...p, pageIndex })), [
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setPagination,
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]);
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const onSort = useCallback(sc => setSortingColumns(sc), [setSortingColumns]);
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return (
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<EuiDataGrid
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aria-label={i18n.translate(
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'xpack.ml.dataframe.analytics.classificationExploration.dataGridAriaLabel',
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{
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defaultMessage: 'Classification results table',
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}
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)}
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columns={columns}
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columnVisibility={{
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visibleColumns: selectedFields,
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setVisibleColumns: setSelectedFields,
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}}
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gridStyle={euiDataGridStyle}
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rowCount={rowCount}
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renderCellValue={renderCellValue}
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sorting={{ columns: sortingColumns, onSort }}
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toolbarVisibility={euiDataGridToolbarSettings}
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pagination={{
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...pagination,
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pageSizeOptions: PAGE_SIZE_OPTIONS,
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onChangeItemsPerPage,
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onChangePage,
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}}
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/>
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);
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};
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@ -117,13 +117,7 @@ export const EvaluatePanel: FC<Props> = ({ jobConfig, jobStatus, searchQuery })
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const resultsField = jobConfig.dest.results_field;
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let requiresKeyword = false;
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const loadData = async ({
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isTrainingClause,
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ignoreDefaultQuery = true,
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}: {
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isTrainingClause: { query: string; operator: string };
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ignoreDefaultQuery?: boolean;
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}) => {
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const loadData = async ({ isTraining }: { isTraining: boolean | undefined }) => {
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setIsLoading(true);
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try {
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@ -134,19 +128,18 @@ export const EvaluatePanel: FC<Props> = ({ jobConfig, jobStatus, searchQuery })
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}
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const evalData = await loadEvalData({
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isTraining: false,
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isTraining,
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index,
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dependentVariable,
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resultsField,
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predictionFieldName,
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searchQuery,
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ignoreDefaultQuery,
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jobType: ANALYSIS_CONFIG_TYPE.CLASSIFICATION,
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requiresKeyword,
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});
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const docsCountResp = await loadDocsCount({
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isTraining: false,
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isTraining,
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searchQuery,
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resultsField,
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destIndex: jobConfig.dest.index,
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@ -225,29 +218,46 @@ export const EvaluatePanel: FC<Props> = ({ jobConfig, jobStatus, searchQuery })
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}, [confusionMatrixData]);
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useEffect(() => {
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const hasIsTrainingClause =
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isResultsSearchBoolQuery(searchQuery) &&
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searchQuery.bool.must.filter(
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(clause: any) => clause.match && clause.match[`${resultsField}.is_training`] !== undefined
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);
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const isTrainingClause =
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hasIsTrainingClause &&
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hasIsTrainingClause[0] &&
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hasIsTrainingClause[0].match[`${resultsField}.is_training`];
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let isTraining: boolean | undefined;
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const query =
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isResultsSearchBoolQuery(searchQuery) && (searchQuery.bool.should || searchQuery.bool.filter);
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const noTrainingQuery = isTrainingClause === false || isTrainingClause === undefined;
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if (query !== undefined && query !== false) {
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for (let i = 0; i < query.length; i++) {
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const clause = query[i];
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if (noTrainingQuery) {
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if (clause.match && clause.match[`${resultsField}.is_training`] !== undefined) {
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isTraining = clause.match[`${resultsField}.is_training`];
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break;
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} else if (
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clause.bool &&
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(clause.bool.should !== undefined || clause.bool.filter !== undefined)
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) {
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const innerQuery = clause.bool.should || clause.bool.filter;
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if (innerQuery !== undefined) {
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for (let j = 0; j < innerQuery.length; j++) {
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const innerClause = innerQuery[j];
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if (
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innerClause.match &&
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innerClause.match[`${resultsField}.is_training`] !== undefined
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) {
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isTraining = innerClause.match[`${resultsField}.is_training`];
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break;
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}
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}
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}
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}
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}
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}
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if (isTraining === undefined) {
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setDataSubsetTitle(SUBSET_TITLE.ENTIRE);
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} else {
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setDataSubsetTitle(
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isTrainingClause && isTrainingClause.query === 'true'
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? SUBSET_TITLE.TRAINING
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: SUBSET_TITLE.TESTING
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isTraining && isTraining === true ? SUBSET_TITLE.TRAINING : SUBSET_TITLE.TESTING
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);
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}
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loadData({ isTrainingClause });
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loadData({ isTraining });
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}, [JSON.stringify(searchQuery)]);
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const renderCellValue = ({
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@ -4,71 +4,39 @@
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* you may not use this file except in compliance with the Elastic License.
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*/
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import React, { Fragment, FC, useEffect, useState } from 'react';
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import moment from 'moment-timezone';
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import React, { Fragment, FC, useEffect } from 'react';
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import { i18n } from '@kbn/i18n';
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import {
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EuiBadge,
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EuiButtonIcon,
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EuiCallOut,
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EuiCheckbox,
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EuiFlexGroup,
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EuiFlexItem,
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EuiFormRow,
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EuiPanel,
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EuiPopover,
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EuiPopoverTitle,
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EuiProgress,
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EuiSpacer,
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EuiText,
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EuiToolTip,
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Query,
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} from '@elastic/eui';
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import { Query as QueryType } from '../../../analytics_management/components/analytics_list/common';
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import { ES_FIELD_TYPES } from '../../../../../../../../../../src/plugins/data/public';
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import { mlFieldFormatService } from '../../../../../services/field_format_service';
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import { IndexPattern } from '../../../../../../../../../../src/plugins/data/public';
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import {
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ColumnType,
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mlInMemoryTableBasicFactory,
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OnTableChangeArg,
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SortingPropType,
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SORT_DIRECTION,
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} from '../../../../../components/ml_in_memory_table';
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import { formatHumanReadableDateTimeSeconds } from '../../../../../util/date_utils';
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import { Field } from '../../../../../../../common/types/fields';
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import { SavedSearchQuery } from '../../../../../contexts/ml';
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import {
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BASIC_NUMERICAL_TYPES,
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EXTENDED_NUMERICAL_TYPES,
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isKeywordAndTextType,
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sortRegressionResultsFields,
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} from '../../../../common/fields';
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import {
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toggleSelectedField,
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EsDoc,
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DataFrameAnalyticsConfig,
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EsFieldName,
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MAX_COLUMNS,
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getPredictedFieldName,
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INDEX_STATUS,
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SEARCH_SIZE,
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defaultSearchQuery,
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getDependentVar,
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} from '../../../../common';
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import { getTaskStateBadge } from '../../../analytics_management/components/analytics_list/columns';
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import { DATA_FRAME_TASK_STATE } from '../../../analytics_management/components/analytics_list/common';
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import { useExploreData, TableItem } from './use_explore_data';
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import { useExploreData } from './use_explore_data'; // TableItem
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import { ExplorationTitle } from './classification_exploration';
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const PAGE_SIZE_OPTIONS = [5, 10, 25, 50];
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const MlInMemoryTableBasic = mlInMemoryTableBasicFactory<TableItem>();
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import { ClassificationExplorationDataGrid } from './classification_exploration_data_grid';
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import { ExplorationQueryBar } from '../exploration_query_bar';
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const showingDocs = i18n.translate(
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'xpack.ml.dataframe.analytics.classificationExploration.documentsShownHelpText',
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@ -94,307 +62,65 @@ interface Props {
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export const ResultsTable: FC<Props> = React.memo(
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({ indexPattern, jobConfig, jobStatus, setEvaluateSearchQuery }) => {
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const [pageIndex, setPageIndex] = useState(0);
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const [pageSize, setPageSize] = useState(25);
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const [selectedFields, setSelectedFields] = useState([] as Field[]);
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const [docFields, setDocFields] = useState([] as Field[]);
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const [depVarType, setDepVarType] = useState<ES_FIELD_TYPES | undefined>(undefined);
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const [isColumnsPopoverVisible, setColumnsPopoverVisible] = useState(false);
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const [searchQuery, setSearchQuery] = useState<SavedSearchQuery>(defaultSearchQuery);
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const [searchError, setSearchError] = useState<any>(undefined);
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const [searchString, setSearchString] = useState<string | undefined>(undefined);
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const predictedFieldName = getPredictedFieldName(
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jobConfig.dest.results_field,
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jobConfig.analysis
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);
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const dependentVariable = getDependentVar(jobConfig.analysis);
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function toggleColumnsPopover() {
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setColumnsPopoverVisible(!isColumnsPopoverVisible);
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}
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function closeColumnsPopover() {
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setColumnsPopoverVisible(false);
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}
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function toggleColumn(column: EsFieldName) {
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if (tableItems.length > 0 && jobConfig !== undefined) {
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// spread to a new array otherwise the component wouldn't re-render
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setSelectedFields([
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...toggleSelectedField(selectedFields, column, jobConfig.dest.results_field, depVarType),
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]);
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}
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}
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const needsDestIndexFields = indexPattern && indexPattern.title === jobConfig.source.index[0];
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const resultsField = jobConfig.dest.results_field;
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const {
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errorMessage,
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loadExploreData,
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sortField,
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sortDirection,
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status,
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tableItems,
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} = useExploreData(
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jobConfig,
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needsDestIndexFields,
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fieldTypes,
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pagination,
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searchQuery,
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selectedFields,
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rowCount,
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setPagination,
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setSearchQuery,
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setSelectedFields,
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setDocFields,
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setDepVarType
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);
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setSortingColumns,
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sortingColumns,
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status,
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tableFields,
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tableItems,
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} = useExploreData(jobConfig, needsDestIndexFields);
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const columns: Array<ColumnType<TableItem>> = selectedFields
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.sort(({ name: a }, { name: b }) => sortRegressionResultsFields(a, b, jobConfig))
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.map(field => {
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const { type } = field;
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let format: any;
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useEffect(() => {
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setEvaluateSearchQuery(searchQuery);
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}, [JSON.stringify(searchQuery)]);
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if (indexPattern !== undefined) {
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format = mlFieldFormatService.getFieldFormatFromIndexPattern(indexPattern, field.id, '');
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}
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const columns = tableFields
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.sort((a: any, b: any) => sortRegressionResultsFields(a, b, jobConfig))
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.map((field: any) => {
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// Built-in values are ['boolean', 'currency', 'datetime', 'numeric', 'json']
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// To fall back to the default string schema it needs to be undefined.
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let schema;
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let isSortable = true;
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const type = fieldTypes[field];
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const isNumber =
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type !== undefined &&
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(BASIC_NUMERICAL_TYPES.has(type) || EXTENDED_NUMERICAL_TYPES.has(type));
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const column: ColumnType<TableItem> = {
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field: field.name,
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name: field.name,
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sortable: true,
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truncateText: true,
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};
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const render = (d: any, fullItem: EsDoc) => {
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if (format !== undefined) {
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d = format.convert(d, 'text');
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return d;
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}
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if (Array.isArray(d) && d.every(item => typeof item === 'string')) {
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// If the cells data is an array of strings, return as a comma separated list.
|
||||
// The list will get limited to 5 items with `…` at the end if there's more in the original array.
|
||||
return `${d.slice(0, 5).join(', ')}${d.length > 5 ? ', …' : ''}`;
|
||||
} else if (Array.isArray(d)) {
|
||||
// If the cells data is an array of e.g. objects, display a 'array' badge with a
|
||||
// tooltip that explains that this type of field is not supported in this table.
|
||||
return (
|
||||
<EuiToolTip
|
||||
content={i18n.translate(
|
||||
'xpack.ml.dataframe.analytics.classificationExploration.indexArrayToolTipContent',
|
||||
{
|
||||
defaultMessage:
|
||||
'The full content of this array based column cannot be displayed.',
|
||||
}
|
||||
)}
|
||||
>
|
||||
<EuiBadge>
|
||||
{i18n.translate(
|
||||
'xpack.ml.dataframe.analytics.classificationExploration.indexArrayBadgeContent',
|
||||
{
|
||||
defaultMessage: 'array',
|
||||
}
|
||||
)}
|
||||
</EuiBadge>
|
||||
</EuiToolTip>
|
||||
);
|
||||
}
|
||||
|
||||
return d;
|
||||
};
|
||||
|
||||
if (isNumber) {
|
||||
column.dataType = 'number';
|
||||
column.render = render;
|
||||
} else if (typeof type !== 'undefined') {
|
||||
switch (type) {
|
||||
case ES_FIELD_TYPES.BOOLEAN:
|
||||
column.dataType = ES_FIELD_TYPES.BOOLEAN;
|
||||
column.render = d => (d ? 'true' : 'false');
|
||||
break;
|
||||
case ES_FIELD_TYPES.DATE:
|
||||
column.align = 'right';
|
||||
if (format !== undefined) {
|
||||
column.render = render;
|
||||
} else {
|
||||
column.render = (d: any) => {
|
||||
if (d !== undefined) {
|
||||
return formatHumanReadableDateTimeSeconds(moment(d).unix() * 1000);
|
||||
}
|
||||
return d;
|
||||
};
|
||||
}
|
||||
break;
|
||||
default:
|
||||
column.render = render;
|
||||
break;
|
||||
}
|
||||
} else {
|
||||
column.render = render;
|
||||
schema = 'numeric';
|
||||
}
|
||||
|
||||
return column;
|
||||
switch (type) {
|
||||
case 'date':
|
||||
schema = 'datetime';
|
||||
break;
|
||||
case 'geo_point':
|
||||
schema = 'json';
|
||||
break;
|
||||
case 'boolean':
|
||||
schema = 'boolean';
|
||||
break;
|
||||
}
|
||||
|
||||
if (field === `${resultsField}.feature_importance`) {
|
||||
isSortable = false;
|
||||
}
|
||||
|
||||
return { id: field, schema, isSortable };
|
||||
});
|
||||
|
||||
const docFieldsCount = docFields.length;
|
||||
|
||||
useEffect(() => {
|
||||
if (
|
||||
jobConfig !== undefined &&
|
||||
columns.length > 0 &&
|
||||
selectedFields.length > 0 &&
|
||||
sortField !== undefined &&
|
||||
sortDirection !== undefined &&
|
||||
selectedFields.some(field => field.name === sortField)
|
||||
) {
|
||||
let field = sortField;
|
||||
// If sorting by predictedField use dependentVar type
|
||||
if (predictedFieldName === sortField) {
|
||||
field = dependentVariable;
|
||||
}
|
||||
const requiresKeyword = isKeywordAndTextType(field);
|
||||
|
||||
loadExploreData({
|
||||
field: sortField,
|
||||
direction: sortDirection,
|
||||
searchQuery,
|
||||
requiresKeyword,
|
||||
});
|
||||
}
|
||||
}, [JSON.stringify(searchQuery)]);
|
||||
|
||||
useEffect(() => {
|
||||
// By default set sorting to descending on the prediction field (`<dependent_varible or prediction_field_name>_prediction`).
|
||||
// if that's not available sort ascending on the first column. Check if the current sorting field is still available.
|
||||
if (
|
||||
jobConfig !== undefined &&
|
||||
columns.length > 0 &&
|
||||
selectedFields.length > 0 &&
|
||||
!selectedFields.some(field => field.name === sortField)
|
||||
) {
|
||||
const predictedFieldSelected = selectedFields.some(
|
||||
field => field.name === predictedFieldName
|
||||
);
|
||||
|
||||
// CHECK IF keyword suffix is needed (if predicted field is selected we have to check the dependent variable type)
|
||||
let sortByField = predictedFieldSelected ? dependentVariable : selectedFields[0].name;
|
||||
|
||||
const requiresKeyword = isKeywordAndTextType(sortByField);
|
||||
|
||||
sortByField = predictedFieldSelected ? predictedFieldName : sortByField;
|
||||
|
||||
const direction = predictedFieldSelected ? SORT_DIRECTION.DESC : SORT_DIRECTION.ASC;
|
||||
loadExploreData({ field: sortByField, direction, searchQuery, requiresKeyword });
|
||||
}
|
||||
}, [
|
||||
jobConfig,
|
||||
columns.length,
|
||||
selectedFields.length,
|
||||
sortField,
|
||||
sortDirection,
|
||||
tableItems.length,
|
||||
]);
|
||||
|
||||
let sorting: SortingPropType = false;
|
||||
let onTableChange;
|
||||
|
||||
if (columns.length > 0 && sortField !== '' && sortField !== undefined) {
|
||||
sorting = {
|
||||
sort: {
|
||||
field: sortField,
|
||||
direction: sortDirection,
|
||||
},
|
||||
};
|
||||
|
||||
onTableChange = ({
|
||||
page = { index: 0, size: 10 },
|
||||
sort = { field: sortField, direction: sortDirection },
|
||||
}: OnTableChangeArg) => {
|
||||
const { index, size } = page;
|
||||
setPageIndex(index);
|
||||
setPageSize(size);
|
||||
|
||||
if (sort.field !== sortField || sort.direction !== sortDirection) {
|
||||
let field = sort.field;
|
||||
// If sorting by predictedField use depVar for type check
|
||||
if (predictedFieldName === sort.field) {
|
||||
field = dependentVariable;
|
||||
}
|
||||
|
||||
loadExploreData({
|
||||
...sort,
|
||||
searchQuery,
|
||||
requiresKeyword: isKeywordAndTextType(field),
|
||||
});
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
const pagination = {
|
||||
initialPageIndex: pageIndex,
|
||||
initialPageSize: pageSize,
|
||||
totalItemCount: tableItems.length,
|
||||
pageSizeOptions: PAGE_SIZE_OPTIONS,
|
||||
hidePerPageOptions: false,
|
||||
};
|
||||
|
||||
const onQueryChange = ({ query, error }: { query: QueryType; error: any }) => {
|
||||
if (error) {
|
||||
setSearchError(error.message);
|
||||
} else {
|
||||
try {
|
||||
const esQueryDsl = Query.toESQuery(query);
|
||||
setSearchQuery(esQueryDsl);
|
||||
setSearchString(query.text);
|
||||
setSearchError(undefined);
|
||||
// set query for use in evaluate panel
|
||||
setEvaluateSearchQuery(esQueryDsl);
|
||||
} catch (e) {
|
||||
setSearchError(e.toString());
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
const search = {
|
||||
onChange: onQueryChange,
|
||||
defaultQuery: searchString,
|
||||
box: {
|
||||
incremental: false,
|
||||
placeholder: i18n.translate(
|
||||
'xpack.ml.dataframe.analytics.regressionExploration.searchBoxPlaceholder',
|
||||
{
|
||||
defaultMessage: 'E.g. avg>0.5',
|
||||
}
|
||||
),
|
||||
},
|
||||
filters: [
|
||||
{
|
||||
type: 'field_value_toggle_group',
|
||||
field: `${jobConfig.dest.results_field}.is_training`,
|
||||
items: [
|
||||
{
|
||||
value: false,
|
||||
name: i18n.translate(
|
||||
'xpack.ml.dataframe.analytics.regressionExploration.isTestingLabel',
|
||||
{
|
||||
defaultMessage: 'Testing',
|
||||
}
|
||||
),
|
||||
},
|
||||
{
|
||||
value: true,
|
||||
name: i18n.translate(
|
||||
'xpack.ml.dataframe.analytics.regressionExploration.isTrainingLabel',
|
||||
{
|
||||
defaultMessage: 'Training',
|
||||
}
|
||||
),
|
||||
},
|
||||
],
|
||||
},
|
||||
],
|
||||
};
|
||||
const docFieldsCount = tableFields.length;
|
||||
|
||||
if (jobConfig === undefined) {
|
||||
return null;
|
||||
|
|
@ -426,11 +152,6 @@ export const ResultsTable: FC<Props> = React.memo(
|
|||
);
|
||||
}
|
||||
|
||||
const tableError =
|
||||
status === INDEX_STATUS.ERROR && errorMessage.includes('parsing_exception')
|
||||
? errorMessage
|
||||
: searchError;
|
||||
|
||||
return (
|
||||
<EuiPanel
|
||||
grow={false}
|
||||
|
|
@ -456,7 +177,7 @@ export const ResultsTable: FC<Props> = React.memo(
|
|||
{docFieldsCount > MAX_COLUMNS && (
|
||||
<EuiText size="s">
|
||||
{i18n.translate(
|
||||
'xpack.ml.dataframe.analytics.regressionExploration.fieldSelection',
|
||||
'xpack.ml.dataframe.analytics.classificationExploration.fieldSelection',
|
||||
{
|
||||
defaultMessage:
|
||||
'{selectedFieldsLength, number} of {docFieldsCount, number} {docFieldsCount, plural, one {field} other {fields}} selected',
|
||||
|
|
@ -466,52 +187,6 @@ export const ResultsTable: FC<Props> = React.memo(
|
|||
</EuiText>
|
||||
)}
|
||||
</EuiFlexItem>
|
||||
<EuiFlexItem grow={false}>
|
||||
<EuiText size="s">
|
||||
<EuiPopover
|
||||
id="popover"
|
||||
button={
|
||||
<EuiButtonIcon
|
||||
iconType="gear"
|
||||
onClick={toggleColumnsPopover}
|
||||
aria-label={i18n.translate(
|
||||
'xpack.ml.dataframe.analytics.regressionExploration.selectColumnsAriaLabel',
|
||||
{
|
||||
defaultMessage: 'Select columns',
|
||||
}
|
||||
)}
|
||||
/>
|
||||
}
|
||||
isOpen={isColumnsPopoverVisible}
|
||||
closePopover={closeColumnsPopover}
|
||||
ownFocus
|
||||
>
|
||||
<EuiPopoverTitle>
|
||||
{i18n.translate(
|
||||
'xpack.ml.dataframe.analytics.regressionExploration.selectFieldsPopoverTitle',
|
||||
{
|
||||
defaultMessage: 'Select fields',
|
||||
}
|
||||
)}
|
||||
</EuiPopoverTitle>
|
||||
<div style={{ maxHeight: '400px', overflowY: 'scroll' }}>
|
||||
{docFields.map(({ name }) => (
|
||||
<EuiCheckbox
|
||||
key={name}
|
||||
id={name}
|
||||
label={name}
|
||||
checked={selectedFields.some(field => field.name === name)}
|
||||
onChange={() => toggleColumn(name)}
|
||||
disabled={
|
||||
selectedFields.some(field => field.name === name) &&
|
||||
selectedFields.length === 1
|
||||
}
|
||||
/>
|
||||
))}
|
||||
</div>
|
||||
</EuiPopover>
|
||||
</EuiText>
|
||||
</EuiFlexItem>
|
||||
</EuiFlexGroup>
|
||||
</EuiFlexItem>
|
||||
</EuiFlexGroup>
|
||||
|
|
@ -520,28 +195,39 @@ export const ResultsTable: FC<Props> = React.memo(
|
|||
<EuiProgress size="xs" color="accent" max={1} value={0} />
|
||||
)}
|
||||
{(columns.length > 0 || searchQuery !== defaultSearchQuery) && (
|
||||
<Fragment>
|
||||
<EuiFormRow
|
||||
helpText={tableItems.length === SEARCH_SIZE ? showingFirstDocs : showingDocs}
|
||||
>
|
||||
<Fragment />
|
||||
</EuiFormRow>
|
||||
<EuiSpacer />
|
||||
<MlInMemoryTableBasic
|
||||
allowNeutralSort={false}
|
||||
columns={columns}
|
||||
compressed
|
||||
hasActions={false}
|
||||
isSelectable={false}
|
||||
items={tableItems}
|
||||
onTableChange={onTableChange}
|
||||
pagination={pagination}
|
||||
responsive={false}
|
||||
search={search}
|
||||
error={tableError}
|
||||
sorting={sorting}
|
||||
/>
|
||||
</Fragment>
|
||||
<EuiFlexGroup direction="column">
|
||||
<EuiFlexItem grow={false}>
|
||||
<EuiSpacer size="s" />
|
||||
<EuiFlexGroup justifyContent="spaceBetween">
|
||||
<EuiFlexItem>
|
||||
<ExplorationQueryBar
|
||||
indexPattern={indexPattern}
|
||||
setSearchQuery={setSearchQuery}
|
||||
/>
|
||||
</EuiFlexItem>
|
||||
</EuiFlexGroup>
|
||||
<EuiFormRow
|
||||
helpText={tableItems.length === SEARCH_SIZE ? showingFirstDocs : showingDocs}
|
||||
>
|
||||
<Fragment />
|
||||
</EuiFormRow>
|
||||
</EuiFlexItem>
|
||||
<EuiFlexItem grow={false}>
|
||||
<ClassificationExplorationDataGrid
|
||||
columns={columns}
|
||||
indexPattern={indexPattern}
|
||||
pagination={pagination}
|
||||
resultsField={jobConfig.dest.results_field}
|
||||
rowCount={rowCount}
|
||||
selectedFields={selectedFields}
|
||||
setPagination={setPagination}
|
||||
setSelectedFields={setSelectedFields}
|
||||
setSortingColumns={setSortingColumns}
|
||||
sortingColumns={sortingColumns}
|
||||
tableItems={tableItems}
|
||||
/>
|
||||
</EuiFlexItem>
|
||||
</EuiFlexGroup>
|
||||
)}
|
||||
</EuiPanel>
|
||||
);
|
||||
|
|
|
|||
|
|
@ -3,113 +3,158 @@
|
|||
* or more contributor license agreements. Licensed under the Elastic License;
|
||||
* you may not use this file except in compliance with the Elastic License.
|
||||
*/
|
||||
/*
|
||||
* Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
|
||||
* or more contributor license agreements. Licensed under the Elastic License;
|
||||
* you may not use this file except in compliance with the Elastic License.
|
||||
*/
|
||||
|
||||
import React, { useEffect, useState } from 'react';
|
||||
import { useEffect, useState, Dispatch, SetStateAction } from 'react';
|
||||
import { EuiDataGridPaginationProps, EuiDataGridSorting } from '@elastic/eui';
|
||||
|
||||
import { SearchResponse } from 'elasticsearch';
|
||||
import { cloneDeep } from 'lodash';
|
||||
|
||||
import { SortDirection, SORT_DIRECTION } from '../../../../../components/ml_in_memory_table';
|
||||
import { SORT_DIRECTION } from '../../../../../components/ml_in_memory_table';
|
||||
|
||||
import { ml } from '../../../../../services/ml_api_service';
|
||||
import { getNestedProperty } from '../../../../../util/object_utils';
|
||||
import { newJobCapsService } from '../../../../../services/new_job_capabilities_service';
|
||||
import { Field } from '../../../../../../../common/types/fields';
|
||||
import { isKeywordAndTextType } from '../../../../common/fields';
|
||||
import { Dictionary } from '../../../../../../../common/types/common';
|
||||
import { ES_FIELD_TYPES } from '../../../../../../../../../../src/plugins/data/public';
|
||||
import {
|
||||
defaultSearchQuery,
|
||||
ResultsSearchQuery,
|
||||
isResultsSearchBoolQuery,
|
||||
LoadExploreDataArg,
|
||||
} from '../../../../common/analytics';
|
||||
|
||||
import {
|
||||
getDefaultFieldsFromJobCaps,
|
||||
getDependentVar,
|
||||
getFlattenedFields,
|
||||
getPredictedFieldName,
|
||||
DataFrameAnalyticsConfig,
|
||||
EsFieldName,
|
||||
INDEX_STATUS,
|
||||
SEARCH_SIZE,
|
||||
SearchQuery,
|
||||
} from '../../../../common';
|
||||
import { SavedSearchQuery } from '../../../../../contexts/ml';
|
||||
|
||||
interface LoadClassificationExploreDataArg {
|
||||
direction: SortDirection;
|
||||
filterByIsTraining?: boolean;
|
||||
field: string;
|
||||
searchQuery: SavedSearchQuery;
|
||||
requiresKeyword?: boolean;
|
||||
pageIndex?: number;
|
||||
pageSize?: number;
|
||||
}
|
||||
|
||||
export type TableItem = Record<string, any>;
|
||||
type Pagination = Pick<EuiDataGridPaginationProps, 'pageIndex' | 'pageSize'>;
|
||||
|
||||
export interface UseExploreDataReturnType {
|
||||
errorMessage: string;
|
||||
loadExploreData: (arg: LoadClassificationExploreDataArg) => void;
|
||||
sortField: EsFieldName;
|
||||
sortDirection: SortDirection;
|
||||
fieldTypes: { [key: string]: ES_FIELD_TYPES };
|
||||
pagination: Pagination;
|
||||
rowCount: number;
|
||||
searchQuery: SavedSearchQuery;
|
||||
selectedFields: EsFieldName[];
|
||||
setFilterByIsTraining: Dispatch<SetStateAction<undefined | boolean>>;
|
||||
setPagination: Dispatch<SetStateAction<Pagination>>;
|
||||
setSearchQuery: Dispatch<SetStateAction<SavedSearchQuery>>;
|
||||
setSelectedFields: Dispatch<SetStateAction<EsFieldName[]>>;
|
||||
setSortingColumns: Dispatch<SetStateAction<EuiDataGridSorting['columns']>>;
|
||||
sortingColumns: EuiDataGridSorting['columns'];
|
||||
status: INDEX_STATUS;
|
||||
tableFields: string[];
|
||||
tableItems: TableItem[];
|
||||
}
|
||||
|
||||
type EsSorting = Dictionary<{
|
||||
order: 'asc' | 'desc';
|
||||
}>;
|
||||
|
||||
// The types specified in `@types/elasticsearch` are out of date and still have `total: number`.
|
||||
interface SearchResponse7 extends SearchResponse<any> {
|
||||
hits: SearchResponse<any>['hits'] & {
|
||||
total: {
|
||||
value: number;
|
||||
relation: string;
|
||||
};
|
||||
};
|
||||
}
|
||||
|
||||
export const useExploreData = (
|
||||
jobConfig: DataFrameAnalyticsConfig | undefined,
|
||||
needsDestIndexFields: boolean,
|
||||
selectedFields: Field[],
|
||||
setSelectedFields: React.Dispatch<React.SetStateAction<Field[]>>,
|
||||
setDocFields: React.Dispatch<React.SetStateAction<Field[]>>,
|
||||
setDepVarType: React.Dispatch<React.SetStateAction<ES_FIELD_TYPES | undefined>>
|
||||
jobConfig: DataFrameAnalyticsConfig,
|
||||
needsDestIndexFields: boolean
|
||||
): UseExploreDataReturnType => {
|
||||
const [errorMessage, setErrorMessage] = useState('');
|
||||
const [status, setStatus] = useState(INDEX_STATUS.UNUSED);
|
||||
|
||||
const [selectedFields, setSelectedFields] = useState([] as EsFieldName[]);
|
||||
const [tableFields, setTableFields] = useState<string[]>([]);
|
||||
const [tableItems, setTableItems] = useState<TableItem[]>([]);
|
||||
const [sortField, setSortField] = useState<string>('');
|
||||
const [sortDirection, setSortDirection] = useState<SortDirection>(SORT_DIRECTION.ASC);
|
||||
const [fieldTypes, setFieldTypes] = useState<{ [key: string]: ES_FIELD_TYPES }>({});
|
||||
const [rowCount, setRowCount] = useState(0);
|
||||
|
||||
const [pagination, setPagination] = useState({ pageIndex: 0, pageSize: 25 });
|
||||
const [searchQuery, setSearchQuery] = useState<SavedSearchQuery>(defaultSearchQuery);
|
||||
const [filterByIsTraining, setFilterByIsTraining] = useState<undefined | boolean>(undefined);
|
||||
const [sortingColumns, setSortingColumns] = useState<EuiDataGridSorting['columns']>([]);
|
||||
|
||||
const predictedFieldName = getPredictedFieldName(
|
||||
jobConfig.dest.results_field,
|
||||
jobConfig.analysis
|
||||
);
|
||||
const dependentVariable = getDependentVar(jobConfig.analysis);
|
||||
|
||||
const getDefaultSelectedFields = () => {
|
||||
const { fields } = newJobCapsService;
|
||||
|
||||
if (selectedFields.length === 0 && jobConfig !== undefined) {
|
||||
const {
|
||||
selectedFields: defaultSelected,
|
||||
docFields,
|
||||
depVarType,
|
||||
} = getDefaultFieldsFromJobCaps(fields, jobConfig, needsDestIndexFields);
|
||||
const { selectedFields: defaultSelected, docFields } = getDefaultFieldsFromJobCaps(
|
||||
fields,
|
||||
jobConfig,
|
||||
needsDestIndexFields
|
||||
);
|
||||
|
||||
setDepVarType(depVarType);
|
||||
setSelectedFields(defaultSelected);
|
||||
setDocFields(docFields);
|
||||
const types: { [key: string]: ES_FIELD_TYPES } = {};
|
||||
const allFields: string[] = [];
|
||||
|
||||
docFields.forEach(field => {
|
||||
types[field.id] = field.type;
|
||||
allFields.push(field.id);
|
||||
});
|
||||
|
||||
setFieldTypes(types);
|
||||
setSelectedFields(defaultSelected.map(field => field.id));
|
||||
setTableFields(allFields);
|
||||
}
|
||||
};
|
||||
|
||||
const loadExploreData = async ({
|
||||
field,
|
||||
direction,
|
||||
searchQuery,
|
||||
requiresKeyword,
|
||||
}: LoadClassificationExploreDataArg) => {
|
||||
filterByIsTraining: isTraining,
|
||||
searchQuery: incomingQuery,
|
||||
}: LoadExploreDataArg) => {
|
||||
if (jobConfig !== undefined) {
|
||||
setErrorMessage('');
|
||||
setStatus(INDEX_STATUS.LOADING);
|
||||
|
||||
try {
|
||||
const resultsField = jobConfig.dest.results_field;
|
||||
const searchQueryClone: ResultsSearchQuery = cloneDeep(searchQuery);
|
||||
const searchQueryClone: ResultsSearchQuery = cloneDeep(incomingQuery);
|
||||
let query: ResultsSearchQuery;
|
||||
const { pageIndex, pageSize } = pagination;
|
||||
// If filterByIsTraining is defined - add that in to the final query
|
||||
const trainingQuery =
|
||||
isTraining !== undefined
|
||||
? {
|
||||
term: { [`${resultsField}.is_training`]: { value: isTraining } },
|
||||
}
|
||||
: undefined;
|
||||
|
||||
if (JSON.stringify(searchQuery) === JSON.stringify(defaultSearchQuery)) {
|
||||
query = {
|
||||
if (JSON.stringify(incomingQuery) === JSON.stringify(defaultSearchQuery)) {
|
||||
const existsQuery = {
|
||||
exists: {
|
||||
field: resultsField,
|
||||
},
|
||||
};
|
||||
|
||||
query = {
|
||||
bool: {
|
||||
must: [existsQuery],
|
||||
},
|
||||
};
|
||||
|
||||
if (trainingQuery !== undefined && isResultsSearchBoolQuery(query)) {
|
||||
query.bool.must.push(trainingQuery);
|
||||
}
|
||||
} else if (isResultsSearchBoolQuery(searchQueryClone)) {
|
||||
if (searchQueryClone.bool.must === undefined) {
|
||||
searchQueryClone.bool.must = [];
|
||||
|
|
@ -121,33 +166,37 @@ export const useExploreData = (
|
|||
},
|
||||
});
|
||||
|
||||
if (trainingQuery !== undefined) {
|
||||
searchQueryClone.bool.must.push(trainingQuery);
|
||||
}
|
||||
|
||||
query = searchQueryClone;
|
||||
} else {
|
||||
query = searchQueryClone;
|
||||
}
|
||||
|
||||
const body: SearchQuery = {
|
||||
query,
|
||||
};
|
||||
const sort: EsSorting = sortingColumns
|
||||
.map(column => {
|
||||
const { id } = column;
|
||||
column.id = isKeywordAndTextType(id) ? `${id}.keyword` : id;
|
||||
return column;
|
||||
})
|
||||
.reduce((s, column) => {
|
||||
s[column.id] = { order: column.direction };
|
||||
return s;
|
||||
}, {} as EsSorting);
|
||||
|
||||
if (field !== undefined) {
|
||||
body.sort = [
|
||||
{
|
||||
[`${field}${requiresKeyword ? '.keyword' : ''}`]: {
|
||||
order: direction,
|
||||
},
|
||||
},
|
||||
];
|
||||
}
|
||||
|
||||
const resp: SearchResponse<any> = await ml.esSearch({
|
||||
const resp: SearchResponse7 = await ml.esSearch({
|
||||
index: jobConfig.dest.index,
|
||||
size: SEARCH_SIZE,
|
||||
body,
|
||||
body: {
|
||||
query,
|
||||
from: pageIndex * pageSize,
|
||||
size: pageSize,
|
||||
...(Object.keys(sort).length > 0 ? { sort } : {}),
|
||||
},
|
||||
});
|
||||
|
||||
setSortField(field);
|
||||
setSortDirection(direction);
|
||||
setRowCount(resp.hits.total.value);
|
||||
|
||||
const docs = resp.hits.hits;
|
||||
|
||||
|
|
@ -199,10 +248,45 @@ export const useExploreData = (
|
|||
};
|
||||
|
||||
useEffect(() => {
|
||||
if (jobConfig !== undefined) {
|
||||
getDefaultSelectedFields();
|
||||
}
|
||||
getDefaultSelectedFields();
|
||||
}, [jobConfig && jobConfig.id]);
|
||||
|
||||
return { errorMessage, loadExploreData, sortField, sortDirection, status, tableItems };
|
||||
// By default set sorting to descending on the prediction field (`<dependent_varible or prediction_field_name>_prediction`).
|
||||
useEffect(() => {
|
||||
const sortByField = isKeywordAndTextType(dependentVariable)
|
||||
? `${predictedFieldName}.keyword`
|
||||
: predictedFieldName;
|
||||
const direction = SORT_DIRECTION.DESC;
|
||||
|
||||
setSortingColumns([{ id: sortByField, direction }]);
|
||||
}, [jobConfig && jobConfig.id]);
|
||||
|
||||
useEffect(() => {
|
||||
loadExploreData({ filterByIsTraining, searchQuery });
|
||||
}, [
|
||||
filterByIsTraining,
|
||||
jobConfig && jobConfig.id,
|
||||
pagination,
|
||||
searchQuery,
|
||||
selectedFields,
|
||||
sortingColumns,
|
||||
]);
|
||||
|
||||
return {
|
||||
errorMessage,
|
||||
fieldTypes,
|
||||
pagination,
|
||||
searchQuery,
|
||||
selectedFields,
|
||||
rowCount,
|
||||
setFilterByIsTraining,
|
||||
setPagination,
|
||||
setSelectedFields,
|
||||
setSortingColumns,
|
||||
setSearchQuery,
|
||||
sortingColumns,
|
||||
status,
|
||||
tableItems,
|
||||
tableFields,
|
||||
};
|
||||
};
|
||||
|
|
|
|||
|
|
@ -29,7 +29,7 @@ import { Dictionary } from '../../../../../../../common/types/common';
|
|||
import { isKeywordAndTextType } from '../../../../common/fields';
|
||||
import { ES_FIELD_TYPES } from '../../../../../../../../../../src/plugins/data/public';
|
||||
import {
|
||||
LoadRegressionExploreDataArg,
|
||||
LoadExploreDataArg,
|
||||
defaultSearchQuery,
|
||||
ResultsSearchQuery,
|
||||
isResultsSearchBoolQuery,
|
||||
|
|
@ -120,7 +120,7 @@ export const useExploreData = (
|
|||
const loadExploreData = async ({
|
||||
filterByIsTraining: isTraining,
|
||||
searchQuery: incomingQuery,
|
||||
}: LoadRegressionExploreDataArg) => {
|
||||
}: LoadExploreDataArg) => {
|
||||
if (jobConfig !== undefined) {
|
||||
setErrorMessage('');
|
||||
setStatus(INDEX_STATUS.LOADING);
|
||||
|
|
|
|||
|
|
@ -9478,8 +9478,6 @@
|
|||
"xpack.ml.dataframe.analytics.classificationExploration.evaluateJobIdTitle": "分類ジョブID {jobId}の評価",
|
||||
"xpack.ml.dataframe.analytics.classificationExploration.firstDocumentsShownHelpText": "予測がある最初の{searchSize}のドキュメントを示す",
|
||||
"xpack.ml.dataframe.analytics.classificationExploration.generalizationDocsCount": "{docsCount, plural, one {# doc} other {# docs}}が評価されました",
|
||||
"xpack.ml.dataframe.analytics.classificationExploration.indexArrayBadgeContent": "配列",
|
||||
"xpack.ml.dataframe.analytics.classificationExploration.indexArrayToolTipContent": "この配列ベースの列の完全なコンテンツは表示できません。",
|
||||
"xpack.ml.dataframe.analytics.classificationExploration.jobCapsFetchError": "結果を取得できません。インデックスのフィールドデータの読み込み中にエラーが発生しました。",
|
||||
"xpack.ml.dataframe.analytics.classificationExploration.jobConfigurationFetchError": "結果を取得できません。ジョブ構成データの読み込み中にエラーが発生しました。",
|
||||
"xpack.ml.dataframe.analytics.classificationExploration.jobConfigurationNoResultsMessage": "結果が見つかりませんでした。",
|
||||
|
|
@ -9574,8 +9572,6 @@
|
|||
"xpack.ml.dataframe.analytics.regressionExploration.generalizationDocsCount": "{docsCount, plural, one {# doc} other {# docs}}が評価されました",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.generalizationErrorTitle": "一般化エラー",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.indexError": "インデックスデータの読み込み中にエラーが発生しました。",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.isTestingLabel": "テスト",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.isTrainingLabel": "トレーニング",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.jobCapsFetchError": "結果を取得できません。インデックスのフィールドデータの読み込み中にエラーが発生しました。",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.jobConfigurationFetchError": "結果を取得できません。ジョブ構成データの読み込み中にエラーが発生しました。",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.meanSquaredErrorText": "平均二乗エラー",
|
||||
|
|
@ -9587,9 +9583,6 @@
|
|||
"xpack.ml.dataframe.analytics.regressionExploration.queryParsingErrorMessage": "クエリをパースできません。",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.rSquaredText": "R の二乗",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.rSquaredTooltipContent": "適合度を表します。モデルによる観察された結果の複製の効果を測定します。",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.searchBoxPlaceholder": "例: 平均>0.5",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.selectColumnsAriaLabel": "列を選択",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.selectFieldsPopoverTitle": "フィールドを選択",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.tableJobIdTitle": "回帰ジョブID {jobId}のデスティネーションインデックス",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.trainingDocsCount": "{docsCount, plural, one {# doc} other {# docs}}が評価されました",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.trainingErrorTitle": "トレーニングエラー",
|
||||
|
|
|
|||
|
|
@ -9481,8 +9481,6 @@
|
|||
"xpack.ml.dataframe.analytics.classificationExploration.evaluateJobIdTitle": "分类作业 ID {jobId} 的评估",
|
||||
"xpack.ml.dataframe.analytics.classificationExploration.firstDocumentsShownHelpText": "正在显示有相关预测存在的前 {searchSize} 个文档",
|
||||
"xpack.ml.dataframe.analytics.classificationExploration.generalizationDocsCount": "{docsCount, plural, one {# 个文档} other {# 个文档}}已评估",
|
||||
"xpack.ml.dataframe.analytics.classificationExploration.indexArrayBadgeContent": "数组",
|
||||
"xpack.ml.dataframe.analytics.classificationExploration.indexArrayToolTipContent": "此基于数组的列的完整内容无法显示。",
|
||||
"xpack.ml.dataframe.analytics.classificationExploration.jobCapsFetchError": "无法提取结果。加载索引的字段数据时发生错误。",
|
||||
"xpack.ml.dataframe.analytics.classificationExploration.jobConfigurationFetchError": "无法提取结果。加载作业配置数据时发生错误。",
|
||||
"xpack.ml.dataframe.analytics.classificationExploration.jobConfigurationNoResultsMessage": "未找到结果。",
|
||||
|
|
@ -9577,8 +9575,6 @@
|
|||
"xpack.ml.dataframe.analytics.regressionExploration.generalizationDocsCount": "{docsCount, plural, one {# 个文档} other {# 个文档}}已评估",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.generalizationErrorTitle": "泛化误差",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.indexError": "加载索引数据时出错。",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.isTestingLabel": "测试",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.isTrainingLabel": "培训",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.jobCapsFetchError": "无法提取结果。加载索引的字段数据时发生错误。",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.jobConfigurationFetchError": "无法提取结果。加载作业配置数据时发生错误。",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.meanSquaredErrorText": "均方误差",
|
||||
|
|
@ -9590,9 +9586,6 @@
|
|||
"xpack.ml.dataframe.analytics.regressionExploration.queryParsingErrorMessage": "无法解析查询。",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.rSquaredText": "R 平方",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.rSquaredTooltipContent": "表示拟合优度。度量模型复制被观察结果的优良性。",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.searchBoxPlaceholder": "例如 avg>0.5",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.selectColumnsAriaLabel": "选择列",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.selectFieldsPopoverTitle": "选择字段",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.tableJobIdTitle": "回归作业 ID {jobId} 的目标索引",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.trainingDocsCount": "{docsCount, plural, one {# 个文档} other {# 个文档}}已评估",
|
||||
"xpack.ml.dataframe.analytics.regressionExploration.trainingErrorTitle": "训练误差",
|
||||
|
|
|
|||
Loading…
Reference in a new issue