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[ML] Data Frame Analytics: Expandable sections for classification and…
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… regression (#79414) (#79517)

Applies the expandable section based layout to the results pages of classification and regression analytics jobs.
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walterra authored Oct 6, 2020
1 parent 649536c commit 9cb4774
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Showing 22 changed files with 919 additions and 857 deletions.
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Expand Up @@ -23,7 +23,7 @@
.mlDataFrameAnalyticsClassification__actualLabel {
float: left;
width: 80px;
padding-top: $euiSize * 4 + $euiSizeXS;
padding-top: $euiSize * 4;
}

/*
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Original file line number Diff line number Diff line change
Expand Up @@ -17,17 +17,19 @@ interface Props {
}

export const ClassificationExploration: FC<Props> = ({ jobId, defaultIsTraining }) => (
<ExplorationPageWrapper
jobId={jobId}
title={i18n.translate(
'xpack.ml.dataframe.analytics.classificationExploration.tableJobIdTitle',
{
defaultMessage: 'Destination index for classification job ID {jobId}',
values: { jobId },
}
)}
EvaluatePanel={EvaluatePanel}
FeatureImportanceSummaryPanel={FeatureImportanceSummaryPanel}
defaultIsTraining={defaultIsTraining}
/>
<div className="mlDataFrameAnalyticsClassification">
<ExplorationPageWrapper
jobId={jobId}
title={i18n.translate(
'xpack.ml.dataframe.analytics.classificationExploration.tableJobIdTitle',
{
defaultMessage: 'Destination index for classification job ID {jobId}',
values: { jobId },
}
)}
EvaluatePanel={EvaluatePanel}
FeatureImportanceSummaryPanel={FeatureImportanceSummaryPanel}
defaultIsTraining={defaultIsTraining}
/>
</div>
);
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Expand Up @@ -6,7 +6,7 @@

import './_classification_exploration.scss';

import React, { FC, useState, useEffect, Fragment } from 'react';
import React, { FC, useState, useEffect } from 'react';
import { i18n } from '@kbn/i18n';
import { FormattedMessage } from '@kbn/i18n/react';
import {
Expand All @@ -15,7 +15,6 @@ import {
EuiFlexGroup,
EuiFlexItem,
EuiIconTip,
EuiPanel,
EuiSpacer,
EuiText,
EuiTitle,
Expand All @@ -30,7 +29,6 @@ import {
DataFrameAnalyticsConfig,
} from '../../../../common';
import { isKeywordAndTextType } from '../../../../common/fields';
import { getTaskStateBadge } from '../../../analytics_management/components/analytics_list/use_columns';
import { DATA_FRAME_TASK_STATE } from '../../../analytics_management/components/analytics_list/common';
import {
isResultsSearchBoolQuery,
Expand All @@ -39,15 +37,17 @@ import {
ResultsSearchQuery,
ANALYSIS_CONFIG_TYPE,
} from '../../../../common/analytics';
import { LoadingPanel } from '../loading_panel';

import { ExpandableSection, HEADER_ITEMS_LOADING } from '../expandable_section';

import {
getColumnData,
ACTUAL_CLASS_ID,
MAX_COLUMNS,
getTrailingControlColumns,
} from './column_data';

interface Props {
export interface EvaluatePanelProps {
jobConfig: DataFrameAnalyticsConfig;
jobStatus?: DATA_FRAME_TASK_STATE;
searchQuery: ResultsSearchQuery;
Expand Down Expand Up @@ -90,7 +90,7 @@ function getHelpText(dataSubsetTitle: string) {
return helpText;
}

export const EvaluatePanel: FC<Props> = ({ jobConfig, jobStatus, searchQuery }) => {
export const EvaluatePanel: FC<EvaluatePanelProps> = ({ jobConfig, jobStatus, searchQuery }) => {
const {
services: { docLinks },
} = useMlKibana();
Expand Down Expand Up @@ -272,10 +272,6 @@ export const EvaluatePanel: FC<Props> = ({ jobConfig, jobStatus, searchQuery })
return <span>{columnId === ACTUAL_CLASS_ID ? cellValue : accuracy}</span>;
};

if (isLoading === true) {
return <LoadingPanel />;
}

const { ELASTIC_WEBSITE_URL, DOC_LINK_VERSION } = docLinks;

const showTrailingColumns = columnsData.length > MAX_COLUMNS;
Expand All @@ -288,137 +284,159 @@ export const EvaluatePanel: FC<Props> = ({ jobConfig, jobStatus, searchQuery })
showTrailingColumns === true && showFullColumns === false ? MAX_COLUMNS : columnsData.length;

return (
<EuiPanel
data-test-subj="mlDFAnalyticsClassificationExplorationEvaluatePanel"
className="mlDataFrameAnalyticsClassification"
>
<div>
<EuiFlexGroup alignItems="center" justifyContent="spaceBetween">
<EuiFlexItem grow={false}>
<EuiTitle size="xs">
<span>
{i18n.translate(
'xpack.ml.dataframe.analytics.classificationExploration.evaluateJobIdTitle',
{
defaultMessage: 'Evaluation of classification job ID {jobId}',
values: { jobId: jobConfig.id },
}
)}
</span>
</EuiTitle>
</EuiFlexItem>
{jobStatus !== undefined && (
<EuiFlexItem grow={false}>
<span>{getTaskStateBadge(jobStatus)}</span>
</EuiFlexItem>
)}
<EuiFlexItem />
<EuiFlexItem grow={false}>
<EuiButtonEmpty
target="_blank"
iconType="help"
iconSide="left"
color="primary"
href={`${ELASTIC_WEBSITE_URL}guide/en/machine-learning/${DOC_LINK_VERSION}/ml-dfanalytics-evaluate.html#ml-dfanalytics-classification`}
>
{i18n.translate(
'xpack.ml.dataframe.analytics.classificationExploration.classificationDocsLink',
{
defaultMessage: 'Classification evaluation docs ',
}
)}
</EuiButtonEmpty>
</EuiFlexItem>
</EuiFlexGroup>
</div>
{error !== null && <ErrorCallout error={error} />}
{error === null && (
<Fragment>
<div>
<EuiFlexGroup gutterSize="xs">
<EuiTitle size="xxs">
<span>{getHelpText(dataSubsetTitle)}</span>
</EuiTitle>
<EuiFlexItem grow={false}>
<EuiIconTip
anchorClassName="mlDataFrameAnalyticsClassificationInfoTooltip"
content={i18n.translate(
'xpack.ml.dataframe.analytics.classificationExploration.confusionMatrixTooltip',
{
defaultMessage:
'The multi-class confusion matrix contains the number of occurrences where the analysis classified data points correctly with their actual class as well as the number of occurrences where it misclassified them with another class',
}
)}
/>
</EuiFlexItem>
</EuiFlexGroup>
</div>
{docsCount !== null && (
<EuiText size="xs" color="subdued">
<FormattedMessage
id="xpack.ml.dataframe.analytics.classificationExploration.generalizationDocsCount"
defaultMessage="{docsCount, plural, one {# doc} other {# docs}} evaluated"
values={{ docsCount }}
/>
</EuiText>
)}
{/* BEGIN TABLE ELEMENTS */}
<EuiSpacer size="m" />
<div className="mlDataFrameAnalyticsClassification__confusionMatrix">
<div className="mlDataFrameAnalyticsClassification__actualLabel">
<EuiText size="xs" color="subdued">
<FormattedMessage
id="xpack.ml.dataframe.analytics.classificationExploration.confusionMatrixActualLabel"
defaultMessage="Actual label"
/>
</EuiText>
</div>
<div className="mlDataFrameAnalyticsClassification__dataGridMinWidth">
{columns.length > 0 && columnsData.length > 0 && (
<>
<ExpandableSection
dataTestId="ClassificationEvaluation"
title={
<FormattedMessage
id="xpack.ml.dataframe.analytics.classificationExploration.evaluateSectionTitle"
defaultMessage="Model evaluation"
/>
}
docsLink={
<EuiButtonEmpty
target="_blank"
iconType="help"
iconSide="left"
color="primary"
href={`${ELASTIC_WEBSITE_URL}guide/en/machine-learning/${DOC_LINK_VERSION}/ml-dfanalytics-evaluate.html#ml-dfanalytics-classification`}
>
{i18n.translate(
'xpack.ml.dataframe.analytics.classificationExploration.classificationDocsLink',
{
defaultMessage: 'Classification evaluation docs ',
}
)}
</EuiButtonEmpty>
}
headerItems={
!isLoading
? [
...(jobStatus !== undefined
? [
{
id: 'jobStatus',
label: i18n.translate(
'xpack.ml.dataframe.analytics.classificationExploration.evaluateJobStatusLabel',
{
defaultMessage: 'Job status',
}
),
value: jobStatus,
},
]
: []),
...(docsCount !== null
? [
{
id: 'docsEvaluated',
label: i18n.translate(
'xpack.ml.dataframe.analytics.classificationExploration.generalizationDocsCount',
{
defaultMessage: '{docsCount, plural, one {doc} other {docs}} evaluated',
values: { docsCount },
}
),
value: docsCount,
},
]
: []),
]
: HEADER_ITEMS_LOADING
}
contentPadding={true}
content={
!isLoading ? (
<>
{error !== null && <ErrorCallout error={error} />}
{error === null && (
<>
<div>
<EuiText size="xs" color="subdued">
<FormattedMessage
id="xpack.ml.dataframe.analytics.classificationExploration.confusionMatrixPredictedLabel"
defaultMessage="Predicted label"
<EuiFlexGroup gutterSize="none">
<EuiTitle size="xxs">
<span>{getHelpText(dataSubsetTitle)}</span>
</EuiTitle>
<EuiFlexItem grow={false}>
<EuiIconTip
anchorClassName="mlDataFrameAnalyticsClassificationInfoTooltip"
content={i18n.translate(
'xpack.ml.dataframe.analytics.classificationExploration.confusionMatrixTooltip',
{
defaultMessage:
'The multi-class confusion matrix contains the number of occurrences where the analysis classified data points correctly with their actual class as well as the number of occurrences where it misclassified them with another class',
}
)}
/>
</EuiText>
</EuiFlexItem>
</EuiFlexGroup>
{/* BEGIN TABLE ELEMENTS */}
<EuiSpacer size="m" />
<div className="mlDataFrameAnalyticsClassification__confusionMatrix">
<div className="mlDataFrameAnalyticsClassification__actualLabel">
<EuiText size="xs" color="subdued">
<FormattedMessage
id="xpack.ml.dataframe.analytics.classificationExploration.confusionMatrixActualLabel"
defaultMessage="Actual label"
/>
</EuiText>
</div>
<div className="mlDataFrameAnalyticsClassification__dataGridMinWidth">
{columns.length > 0 && columnsData.length > 0 && (
<>
<div>
<EuiText size="xs" color="subdued">
<FormattedMessage
id="xpack.ml.dataframe.analytics.classificationExploration.confusionMatrixPredictedLabel"
defaultMessage="Predicted label"
/>
</EuiText>
</div>
<EuiSpacer size="s" />
<EuiDataGrid
data-test-subj="mlDFAnalyticsClassificationExplorationConfusionMatrix"
aria-label={i18n.translate(
'xpack.ml.dataframe.analytics.classificationExploration.confusionMatrixLabel',
{
defaultMessage: 'Classification confusion matrix',
}
)}
columns={shownColumns}
columnVisibility={{ visibleColumns, setVisibleColumns }}
rowCount={rowCount}
renderCellValue={renderCellValue}
inMemory={{ level: 'sorting' }}
toolbarVisibility={{
showColumnSelector: true,
showStyleSelector: false,
showFullScreenSelector: false,
showSortSelector: false,
}}
popoverContents={popoverContents}
gridStyle={{
border: 'all',
fontSize: 's',
cellPadding: 's',
stripes: false,
rowHover: 'none',
header: 'shade',
}}
trailingControlColumns={
showTrailingColumns === true && showFullColumns === false
? getTrailingControlColumns(extraColumns, setShowFullColumns)
: undefined
}
/>
</>
)}
</div>
</div>
<EuiSpacer size="s" />
<EuiDataGrid
data-test-subj="mlDFAnalyticsClassificationExplorationConfusionMatrix"
aria-label={i18n.translate(
'xpack.ml.dataframe.analytics.classificationExploration.confusionMatrixLabel',
{
defaultMessage: 'Classification confusion matrix',
}
)}
columns={shownColumns}
columnVisibility={{ visibleColumns, setVisibleColumns }}
rowCount={rowCount}
renderCellValue={renderCellValue}
inMemory={{ level: 'sorting' }}
toolbarVisibility={{
showColumnSelector: true,
showStyleSelector: false,
showFullScreenSelector: false,
showSortSelector: false,
}}
popoverContents={popoverContents}
gridStyle={{ rowHover: 'none' }}
trailingControlColumns={
showTrailingColumns === true && showFullColumns === false
? getTrailingControlColumns(extraColumns, setShowFullColumns)
: undefined
}
/>
</>
)}
</div>
</div>
</Fragment>
)}
{/* END TABLE ELEMENTS */}
</EuiPanel>
{/* END TABLE ELEMENTS */}
</>
) : null
}
/>
<EuiSpacer size="m" />
</>
);
};
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