docs(samples): add feature importance to predict sample (#277)

* Add feature importance to predict sample

* Fix license header

* fix: skip tensorflow linkinator - flaky

* Add bens map suggestion

* Fix lint and errors

Co-authored-by: Benjamin E. Coe <bencoe@google.com>

automl/tables/predict.v1beta1.js

@@ -63,14 +63,36 @@ async function main(
       // Params is additional domain-specific parameters.
       // Currently there is no additional parameters supported.
       client
-        .predict({name: modelFullId, payload: payload, params: {}})
+        .predict({
+          name: modelFullId,
+          payload: payload,
+          params: {feature_importance: true},
+        })
         .then(responses => {
           console.log(responses);
           console.log(`Prediction results:`);
 
           for (const result of responses[0].payload) {
             console.log(`Predicted class name: ${result.displayName}`);
             console.log(`Predicted class score: ${result.tables.score}`);
+
+            // Get features of top importance
+            const featureList = result.tables.tablesModelColumnInfo.map(
+              columnInfo => {
+                return {
+                  importance: columnInfo.featureImportance,
+                  displayName: columnInfo.columnDisplayName,
+                };
+              }
+            );
+            // Sort features by their importance, highest importance first
+            featureList.sort(function(a, b) {
+              return b.importance - a.importance;
+            });
+
+            // Print top 10 important features
+            console.log('Features of top importance');
+            console.log(featureList.slice(0, 10));
           }
         })
         .catch(err => {

automl/test/automlTablesPredict.v1beta1.test.js

@@ -1,16 +1,17 @@
-// Copyright 2019 Google LLC
-//
-// Licensed under the Apache License, Version 2.0 (the "License");
-// you may not use this file except in compliance with the License.
-// You may obtain a copy of the License at
-//
-//     https://www.apache.org/licenses/LICENSE-2.0
-//
-// Unless required by applicable law or agreed to in writing, software
-// distributed under the License is distributed on an "AS IS" BASIS,
-// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-// See the License for the specific language governing permissions and
-// limitations under the License.
+/**
+ * Copyright 2019 Google LLC
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
 
 'use strict';
 
@@ -42,6 +43,7 @@ describe('Tables PredictionAPI', () => {
     // Run single prediction on predictTest.csv in resource folder
     const output = exec(`${cmdPredict} predict "${modelId}" "${filePath}"`);
     assert.match(output, /Prediction results:/);
+    assert.match(output, /Features of top importance:/);
   });
 
   it.skip(`should perform batch prediction using GCS as source and