Do not fail Evaluate API when the actual and predicted fields' types differ (#54255)

Author: przemekwitek

x-pack/plugin/core/src/main/java/org/elasticsearch/xpack/core/ml/dataframe/evaluation/classification/MulticlassConfusionMatrix.java

@@ -142,7 +142,7 @@ public final Tuple<List<AggregationBuilder>, List<PipelineAggregationBuilder>> a
         if (result.get() == null) {  // These are steps 2, 3, 4 etc.
             KeyedFilter[] keyedFiltersPredicted =
                 topActualClassNames.get().stream()
-                    .map(className -> new KeyedFilter(className, QueryBuilders.termQuery(predictedField, className)))
+                    .map(className -> new KeyedFilter(className, QueryBuilders.matchQuery(predictedField, className).lenient(true)))
                     .toArray(KeyedFilter[]::new);
             // Knowing exactly how many buckets does each aggregation use, we can choose the size of the batch so that
             // too_many_buckets_exception exception is not thrown.
@@ -153,7 +153,7 @@ public final Tuple<List<AggregationBuilder>, List<PipelineAggregationBuilder>> a
                 topActualClassNames.get().stream()
                     .skip(actualClasses.size())
                     .limit(actualClassesPerBatch)
-                    .map(className -> new KeyedFilter(className, QueryBuilders.termQuery(actualField, className)))
+                    .map(className -> new KeyedFilter(className, QueryBuilders.matchQuery(actualField, className).lenient(true)))
                     .toArray(KeyedFilter[]::new);
             if (keyedFiltersActual.length > 0) {
                 return Tuple.tuple(

x-pack/plugin/core/src/main/java/org/elasticsearch/xpack/core/ml/dataframe/evaluation/classification/Precision.java

@@ -107,7 +107,7 @@ public final Tuple<List<AggregationBuilder>, List<PipelineAggregationBuilder>> a
         if (result.get() == null) {  // This is step 2
             KeyedFilter[] keyedFiltersPredicted =
                 topActualClassNames.get().stream()
-                    .map(className -> new KeyedFilter(className, QueryBuilders.termQuery(predictedField, className)))
+                    .map(className -> new KeyedFilter(className, QueryBuilders.matchQuery(predictedField, className).lenient(true)))
                     .toArray(KeyedFilter[]::new);
             Script script = PainlessScripts.buildIsEqualScript(actualField, predictedField);
             return Tuple.tuple(