cross validation unit tests added positive case

test/cross_validator/cross_validator_impl_test.dart

@@ -0,0 +1,62 @@
+import 'dart:typed_data';
+
+import 'package:ml_algo/src/metric/metric_type.dart';
+import 'package:ml_algo/src/model_selection/cross_validator/cross_validator_impl.dart';
+import 'package:ml_algo/src/model_selection/data_splitter/splitter.dart';
+import 'package:ml_linalg/matrix.dart';
+import 'package:mockito/mockito.dart';
+import 'package:test/test.dart';
+
+import '../test_utils/mocks.dart';
+
+Splitter createSplitter(Iterable<Iterable<int>> indices) {
+  final splitter = SplitterMock();
+  when(splitter.split(any)).thenReturn(indices);
+  return splitter;
+}
+
+void main() {
+  group('CrossValidatorImpl', () {
+    test('should perform validation of a model on given test indices of'
+        'observations', () {
+      final allObservations = Matrix.from([
+        [330, 930, 130],
+        [630, 830, 230],
+        [730, 730, 330],
+        [830, 630, 430],
+        [930, 530, 530],
+        [130, 430, 630],
+        [230, 330, 730],
+        [430, 230, 830],
+        [530, 130, 930],
+      ]);
+      final allOutcomes = Matrix.from([
+        [100],[200],[300],[400],[500],[600],[700],[800],[900],
+      ]);
+      final metric = MetricType.mape;
+      final splitter = createSplitter([[0,2,4],[6, 8]]);
+      final predictor = PredictorMock();
+      final validator = CrossValidatorImpl(Float32x4, splitter);
+
+      var score = 20.0;
+      when(predictor.test(any, any, any))
+          .thenAnswer((Invocation inv) => score = score + 10);
+
+      final actual = validator.evaluate((observations, outcomes) => predictor,
+          allObservations, allOutcomes, metric);
+
+      expect(actual, 35);
+
+      verify(predictor.test(argThat(equals([
+        [330, 930, 130],
+        [730, 730, 330],
+        [930, 530, 530],
+      ])), argThat(equals([[100], [300], [500]])), metric)).called(1);
+
+      verify(predictor.test(argThat(equals([
+        [230, 330, 730],
+        [530, 130, 930],
+      ])), argThat(equals([[700], [900]])), metric)).called(1);
+    });
+  });
+}

test/test_all.dart

@@ -6,6 +6,8 @@ import 'classifier/logistic_regressor_integration_test.dart'
 import 'classifier/logistic_regressor_test.dart' as logistic_regressor_test;
 import 'classifier/softmax_regressor_test.dart' as softmax_regressor_test;
 import 'cost_function/cost_function_test.dart' as cost_function_test;
+import 'cross_validator/cross_validator_impl_test.dart'
+  as cross_validator_impl_test;
 import 'data_preprocessing/intercept_preprocessor_test.dart'
     as intercept_preprocessor_test;
 import 'data_splitter/k_fold_splitter_test.dart' as k_fold_splitter_test;
@@ -34,6 +36,7 @@ void main() {
   logistic_regressor_test.main();
   softmax_regressor_test.main();
   cost_function_test.main();
+  cross_validator_impl_test.main();
   intercept_preprocessor_test.main();
   k_fold_splitter_test.main();
   lpo_splitter_test.main();

test/test_utils/mocks.dart

@@ -5,6 +5,7 @@ import 'package:ml_algo/src/data_preprocessing/intercept_preprocessor/intercept_
 import 'package:ml_algo/src/data_preprocessing/intercept_preprocessor/intercept_preprocessor_factory.dart';
 import 'package:ml_algo/src/math/randomizer/randomizer.dart';
 import 'package:ml_algo/src/math/randomizer/randomizer_factory.dart';
+import 'package:ml_algo/src/model_selection/data_splitter/splitter.dart';
 import 'package:ml_algo/src/optimizer/convergence_detector/convergence_detector.dart';
 import 'package:ml_algo/src/optimizer/convergence_detector/convergence_detector_factory.dart';
 import 'package:ml_algo/src/optimizer/gradient/learning_rate_generator/learning_rate_generator.dart';
@@ -16,6 +17,7 @@ import 'package:ml_algo/src/optimizer/initial_weights_generator/initial_weights_
 import 'package:ml_algo/src/optimizer/optimizer.dart';
 import 'package:ml_algo/src/optimizer/optimizer_factory.dart';
 import 'package:ml_algo/src/optimizer/optimizer_type.dart';
+import 'package:ml_algo/src/predictor/predictor.dart';
 import 'package:ml_algo/src/score_to_prob_mapper/score_to_prob_mapper.dart';
 import 'package:ml_algo/src/score_to_prob_mapper/score_to_prob_mapper_factory.dart';
 import 'package:ml_algo/src/score_to_prob_mapper/score_to_prob_mapper_type.dart';
@@ -60,6 +62,10 @@ class ConvergenceDetectorFactoryMock extends Mock
 
 class ConvergenceDetectorMock extends Mock implements ConvergenceDetector {}
 
+class SplitterMock extends Mock implements Splitter {}
+
+class PredictorMock extends Mock implements Predictor {}
+
 LearningRateGeneratorFactoryMock createLearningRateGeneratorFactoryMock({
   Map<LearningRateType, LearningRateGenerator> generators,
 }) {