[ML] Update to new client & more strict conversion

Author: qn895

x-pack/plugins/ml/public/application/components/data_grid/feature_importance/decision_path_classification.tsx

@@ -8,7 +8,11 @@ import React, { FC, useMemo, useState } from 'react';
 import { i18n } from '@kbn/i18n';
 import { EuiHealth, EuiSpacer, EuiSuperSelect, EuiTitle } from '@elastic/eui';
 import d3 from 'd3';
-import { isDecisionPathData, useDecisionPathData } from './use_classification_path_data';
+import {
+  isDecisionPathData,
+  useDecisionPathData,
+  getStringBasedClassName,
+} from './use_classification_path_data';
 import { FeatureImportance, TopClasses } from '../../../../../common/types/feature_importance';
 import { DecisionPathChart } from './decision_path_chart';
 import { MissingDecisionPathCallout } from './missing_decision_path_callout';
@@ -20,27 +24,25 @@ interface ClassificationDecisionPathProps {
   topClasses: TopClasses;
 }
 
-// cast to 'True' | 'False' | value to match Eui display
-const getStr = (v: string | boolean): string =>
-  typeof v === 'boolean' ? (v ? 'True' : 'False') : v;
-
 export const ClassificationDecisionPath: FC<ClassificationDecisionPathProps> = ({
   featureImportance,
   predictedValue,
   topClasses,
   predictionFieldName,
 }) => {
-  const [currentClass, setCurrentClass] = useState<string>(getStr(topClasses[0].class_name));
+  const [currentClass, setCurrentClass] = useState<string>(
+    getStringBasedClassName(topClasses[0].class_name)
+  );
   const { decisionPathData } = useDecisionPathData({
     featureImportance,
     predictedValue: currentClass,
   });
   const options = useMemo(() => {
-    const predictionValueStr = getStr(predictedValue);
+    const predictionValueStr = getStringBasedClassName(predictedValue);
 
     return Array.isArray(topClasses)
       ? topClasses.map((c) => {
-          const className = getStr(c.class_name);
+          const className = getStringBasedClassName(c.class_name);
           return {
             value: className,
             inputDisplay:

x-pack/plugins/ml/public/application/components/data_grid/feature_importance/use_classification_path_data.tsx

@@ -34,6 +34,21 @@ export const isDecisionPathData = (decisionPathData: any): boolean => {
     decisionPathData[0].length === 3
   );
 };
+
+// cast to 'True' | 'False' | value to match Eui display
+export const getStringBasedClassName = (v: string | boolean | undefined | number): string => {
+  if (v === undefined) {
+    return '';
+  }
+  if (typeof v === 'boolean') {
+    return v ? 'True' : 'False';
+  }
+  if (typeof v === 'number') {
+    return v.toString();
+  }
+  return v;
+};
+
 export const useDecisionPathData = ({
   baseline,
   featureImportance,
@@ -139,7 +154,7 @@ export const buildClassificationDecisionPathData = ({
     ExtendedFeatureImportance | undefined
   > = featureImportance.map((feature) => {
     const classFeatureImportance = Array.isArray(feature.classes)
-      ? feature.classes.find((c) => c.class_name === currentClass)
+      ? feature.classes.find((c) => getStringBasedClassName(c.class_name) === currentClass)
       : feature;
     if (classFeatureImportance && typeof classFeatureImportance[FEATURE_IMPORTANCE] === 'number') {
       return {

x-pack/plugins/ml/server/models/data_frame_analytics/feature_importance.ts

@@ -4,20 +4,20 @@
  * you may not use this file except in compliance with the Elastic License.
  */
 
-import { ILegacyScopedClusterClient } from 'kibana/server';
+import { IScopedClusterClient } from 'kibana/server';
 import { getPredictionFieldName, isRegressionAnalysis } from '../../../common/util/analytics_utils';
 
 // Obtains data for the data frame analytics feature importance functionalities
 // such as baseline, decision paths, or importance summary.
 export function analyticsFeatureImportanceProvider({
-  callAsCurrentUser,
-  callAsInternalUser,
-}: ILegacyScopedClusterClient) {
+  asInternalUser,
+  asCurrentUser,
+}: IScopedClusterClient) {
   async function getRegressionAnalyticsBaseline(analyticsId: string): Promise<number | undefined> {
-    const results = await callAsInternalUser('ml.getDataFrameAnalytics', {
-      analyticsId,
+    const { body } = await asInternalUser.ml.getDataFrameAnalytics({
+      id: analyticsId,
     });
-    const jobConfig = results.data_frame_analytics[0];
+    const jobConfig = body.data_frame_analytics[0];
     if (!isRegressionAnalysis) return undefined;
     const destinationIndex = jobConfig.dest.index;
     const predictionField = getPredictionFieldName(jobConfig.analysis);
@@ -46,7 +46,7 @@ export function analyticsFeatureImportanceProvider({
       },
     };
     let baseline;
-    const aggregationResult = await callAsCurrentUser('search', params);
+    const { body: aggregationResult } = await asCurrentUser.search(params);
     if (aggregationResult) {
       baseline = aggregationResult.aggregations.featureImportanceBaseline.value;
     }