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[ML] Fixes incorrect feature importance visualization for Data Frame Analytics classification #150816

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merged 7 commits into from
Feb 14, 2023
Merged

[ML] Fixes incorrect feature importance visualization for Data Frame Analytics classification #150816

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4da12d7
Add fix, add test
qn895 Feb 9, 2023
548f768
Fix row index causing popover to not show up on page >=2
qn895 Feb 10, 2023
08af272
Merge remote-tracking branch 'upstream/main' into dv-fix-classificati…
qn895 Feb 10, 2023
c3f9233
Add tests to check for feature importance when pagination is changed
qn895 Feb 10, 2023
6495166
Merge branch 'main' into dv-fix-classification-path
kibanamachine Feb 13, 2023
bf7b038
Merge branch 'main' into dv-fix-classification-path
kibanamachine Feb 13, 2023
b5a74a4
Merge branch 'main' into dv-fix-classification-path
kibanamachine Feb 14, 2023
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2 changes: 1 addition & 1 deletion x-pack/plugins/ml/public/application/components/data_grid/data_grid.tsx
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Original file line number Diff line number Diff line change
Expand Up @@ -124,7 +124,7 @@ export const DataGrid: FC<Props> = memo(
analysisType === ANALYSIS_CONFIG_TYPE.OUTLIER_DETECTION
) {
if (schema === 'featureImportance') {
const row = data[rowIndex];
const row = data[rowIndex - pagination.pageIndex * pagination.pageSize];
if (!row) return <div />;
// if resultsField for some reason is not available then use ml
const mlResultsField = resultsField ?? DEFAULT_RESULTS_FIELD;
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11 changes: 10 additions & 1 deletion ...ages/analytics_exploration/components/feature_importance/decision_path_classification.tsx
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Expand Up @@ -21,6 +21,7 @@ import type {
} from '../../../../../../../common/types/feature_importance';
import { DecisionPathChart } from './decision_path_chart';
import { MissingDecisionPathCallout } from './missing_decision_path_callout';
import { TopClass } from '../../../../../../../common/types/feature_importance';

interface ClassificationDecisionPathProps {
predictedValue: string | boolean;
Expand All @@ -42,12 +43,20 @@ export const ClassificationDecisionPath: FC<ClassificationDecisionPathProps> = (
const [currentClass, setCurrentClass] = useState<string>(
getStringBasedClassName(topClasses[0].class_name)
);
const selectedClass = topClasses.find(
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The description of the fix refers to True and False base classes, but is this change also the cause of the change in behavior here with the bank_classification_1 MLQA bootstrap job where before I was seeing values greater than 1 for yes and no classes:

Before:

image

With this fix:

image

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AFAICS, the fix makes total sense here: for the second row, the model predicts the class "no" with the probability of 0.986. This means that the prediction probability of "yes" is 0.014. This is precisely what the screenshot above shows now 🚀

The screenshot before this fix shows that the decision graph briefly exceeds 1.0 in for prediction probability, which is nonsense.

(t) => getStringBasedClassName(t.class_name) === getStringBasedClassName(currentClass)
) as TopClass;
const predictedProbabilityForCurrentClass = selectedClass
? selectedClass.class_probability
: undefined;

const { decisionPathData } = useDecisionPathData({
baseline,
featureImportance,
predictedValue: currentClass,
predictedProbability,
predictedProbability: predictedProbabilityForCurrentClass,
});

const options = useMemo(() => {
const predictionValueStr = getStringBasedClassName(predictedValue);

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