Set 'fitIntercept' param to 'true' by default (#234)

Author: gyrdym

CHANGELOG.md

@@ -1,5 +1,9 @@
 # Changelog
 
+## 16.15.2
+- LinearRegressor, LogisticRegressor, SoftmaxRegressor:
+    - Set `fitIntercept` param to `true` by default
+
 ## 16.15.1
 - README: LogisticRegressor example corrected
 

e2e/decision_tree_classifier/iris_tree.svg

@@ -398,7 +398,7 @@ abstract class LogisticRegressor
   /// coefficients, that is also bad.
   ///
   /// [fitIntercept] Whether or not to fit intercept term. Default value is
-  /// `false`. Intercept in 2-dimensional space is a bias of the line (relative
+  /// `true`. Intercept in 2-dimensional space is a bias of the line (relative
   /// to X-axis).
   ///
   /// [interceptScale] A value, defining a size of the intercept.

e2e/decision_tree_classifier/pima_indians_tree.svg

@@ -93,7 +93,7 @@ abstract class SoftmaxRegressor
   /// mode will be activated.
   ///
   /// [fitIntercept] Whether or not to fit intercept term. Default value is
-  /// `false`. Intercept in 2-dimensional space is a bias of the line (relative
+  /// `true`. Intercept in 2-dimensional space is a bias of the line (relative
   /// to X-axis) to be learned by the classifier.
   ///
   /// [interceptScale] A value defining a size of the intercept.

lib/src/classifier/logistic_regressor/logistic_regressor.dart

@@ -3,5 +3,5 @@ import 'package:ml_algo/src/linear_optimizer/linear_optimizer_type.dart';
 
 const initialCoefficientsTypeDefaultValue = InitialCoefficientsType.zeroes;
 const linearOptimizerTypeDefaultValue = LinearOptimizerType.gradient;
-const fitInterceptDefaultValue = false;
+const fitInterceptDefaultValue = true;
 const interceptScaleDefaultValue = 1.0;

lib/src/classifier/softmax_regressor/softmax_regressor.dart

@@ -193,7 +193,7 @@ abstract class LinearRegressor
   /// The greater the value of [lambda], the stricter feature selection is.
   ///
   /// [fitIntercept] Whether or not to fit intercept term. Default value is
-  /// `false`. Intercept in 2-dimensional space is a bias of the line (relative
+  /// `true`. Intercept in 2-dimensional space is a bias of the line (relative
   /// to X-axis).
   ///
   /// [interceptScale] A value defining a size of the intercept.

lib/src/common/constants/default_parameters/linear_optimization.dart

@@ -1,6 +1,6 @@
 name: ml_algo
 description: Machine learning algorithms, Machine learning models performance evaluation functionality
-version: 16.15.1
+version: 16.15.2
 homepage: https://github.com/gyrdym/ml_algo
 
 environment:

lib/src/regressor/linear_regressor/linear_regressor.dart

@@ -327,6 +327,7 @@ void main() {
             batchSize: 3,
             dtype: DType.float32,
             collectLearningData: true,
+            fitIntercept: false,
             iterationsLimit: 3);
 
         expect(classifier.costPerIteration, [

pubspec.yaml

@@ -11,7 +11,7 @@ void main() {
         [5.5, 5, 20],
         [5.25, 5, 22],
       ]);
-      final regressor = LinearRegressor(data, targetName);
+      final regressor = LinearRegressor(data, targetName, fitIntercept: false);
       final dataToPredict = [
         [5, 25.0]
       ];