e2e tests task added

lib/src/classifier/_mixins/linear_classifier_mixin.dart

@@ -12,7 +12,7 @@ mixin LinearClassifierMixin implements LinearClassifier {
 
     return DataFrame.fromMatrix(
       probabilities,
-      header: classNames,
+      header: targetNames,
     );
   }
 

lib/src/classifier/linear_classifier.dart

@@ -4,8 +4,6 @@ import 'package:ml_linalg/matrix.dart';
 
 /// An interface for all types of linear classifiers
 abstract class LinearClassifier implements Classifier {
-  Iterable<String> get classNames;
-
   /// A function that is used for converting learned coefficients into
   /// probabilities
   LinkFunction get linkFunction;

lib/src/classifier/logistic_regressor/logistic_regressor_impl.dart

@@ -30,7 +30,7 @@ class LogisticRegressorImpl
         LogisticRegressor {
 
   LogisticRegressorImpl(
-      this.classNames,
+      this.targetNames,
       this.linkFunction,
       this.fitIntercept,
       this.interceptScale,
@@ -72,9 +72,8 @@ class LogisticRegressorImpl
   final Matrix coefficientsByClasses;
 
   @override
-  @deprecated
   @JsonKey(name: logisticRegressorClassNamesJsonKey)
-  final Iterable<String> classNames;
+  final Iterable<String> targetNames;
 
   @override
   @JsonKey(name: logisticRegressorFitInterceptJsonKey)
@@ -118,9 +117,6 @@ class LogisticRegressorImpl
   )
   final List<num> costPerIteration;
 
-  @override
-  Iterable<String> get targetNames => classNames;
-
   @override
   DataFrame predict(DataFrame testFeatures) {
     final predictedLabels = getProbabilitiesMatrix(testFeatures)

lib/src/classifier/softmax_regressor/softmax_regressor_impl.dart

@@ -27,7 +27,7 @@ class SoftmaxRegressorImpl
 
   SoftmaxRegressorImpl(
       this.coefficientsByClasses,
-      this.classNames,
+      this.targetNames,
       this.linkFunction,
       this.fitIntercept,
       this.interceptScale,
@@ -54,9 +54,8 @@ class SoftmaxRegressorImpl
   Map<String, dynamic> toJson() => _$SoftmaxRegressorImplToJson(this);
 
   @override
-  @deprecated
   @JsonKey(name: softmaxRegressorClassNamesJsonKey)
-  final Iterable<String> classNames;
+  final Iterable<String> targetNames;
 
   @override
   @JsonKey(name: softmaxRegressorFitInterceptJsonKey)
@@ -105,9 +104,6 @@ class SoftmaxRegressorImpl
   )
   final List<num> costPerIteration;
 
-  @override
-  Iterable<String> get targetNames => classNames;
-
   @override
   DataFrame predict(DataFrame testFeatures) {
     final allProbabilities = getProbabilitiesMatrix(testFeatures);

test/classifier/logistic_regressor/integration_test/logistic_regressor_serialization_integration_test.dart

@@ -316,7 +316,7 @@ void main() {
       expect(restoredClassifier.dtype, classifier.dtype);
       expect(restoredClassifier.linkFunction,
           isA<Float32InverseLogitLinkFunction>());
-      expect(restoredClassifier.classNames, [targetName]);
+      expect(restoredClassifier.targetNames, [targetName]);
     });
 
     test('should restore a classifier instance from json file, '
@@ -335,7 +335,7 @@ void main() {
       expect(restoredClassifier.dtype, classifier.dtype);
       expect(restoredClassifier.linkFunction,
           isA<Float64InverseLogitLinkFunction>());
-      expect(restoredClassifier.classNames, [targetName]);
+      expect(restoredClassifier.targetNames, [targetName]);
     });
   });
 }

test/classifier/logistic_regressor/unit_test/logistic_regressor_impl_test.dart

@@ -68,7 +68,7 @@ void main() {
     group('default constructor', () {
       test('should create the instance with `classNames` list of just one '
           'element', () {
-        expect(regressor.classNames, equals([className]));
+        expect(regressor.targetNames, equals([className]));
       });
 
       test('should throw an exception if probability threshold is less '

test/classifier/logistic_regressor/unit_test/logistic_regressor_test.dart

@@ -274,7 +274,7 @@ void main() {
       expect(classifier.fitIntercept, fitIntercept);
       expect(classifier.dtype, dtype);
       expect(classifier.coefficientsByClasses, learnedCoefficients);
-      expect(classifier.classNames, [targetName]);
+      expect(classifier.targetNames, [targetName]);
     });
   });
 }

test/classifier/softmax_regressor/integration_test/softmax_regressor_serialization_integration_test.dart

@@ -230,7 +230,7 @@ void main() {
 
       expect(restoredClassifier.interceptScale, classifier.interceptScale);
       expect(restoredClassifier.fitIntercept, classifier.fitIntercept);
-      expect(restoredClassifier.classNames, classifier.classNames);
+      expect(restoredClassifier.targetNames, classifier.targetNames);
       expect(restoredClassifier.coefficientsByClasses,
           classifier.coefficientsByClasses);
       expect(restoredClassifier.linkFunction.runtimeType,
@@ -249,7 +249,7 @@ void main() {
 
       expect(restoredClassifier.interceptScale, classifier.interceptScale);
       expect(restoredClassifier.fitIntercept, classifier.fitIntercept);
-      expect(restoredClassifier.classNames, classifier.classNames);
+      expect(restoredClassifier.targetNames, classifier.targetNames);
       expect(restoredClassifier.coefficientsByClasses,
           classifier.coefficientsByClasses);
       expect(restoredClassifier.linkFunction.runtimeType,

test/classifier/softmax_regressor/unit_test/softmax_regressor_factory_impl_test.dart

@@ -47,7 +47,7 @@ void main() {
     test('should persist data passed to the `create` method', () {
       expect(regressor.costPerIteration, costPerIteration);
       expect(regressor.dtype, dtype);
-      expect(regressor.classNames, classNames);
+      expect(regressor.targetNames, classNames);
       expect(regressor.interceptScale, interceptScale);
       expect(regressor.linkFunction, linkFunction);
       expect(regressor.fitIntercept, fitIntercept);