From 7798c380c05178e875ebd167dba26fa1095913fe Mon Sep 17 00:00:00 2001
From: Ilya Gyrdymov <ilgyrd@gmail.com>
Date: Fri, 1 Nov 2019 01:08:54 +0200
Subject: [PATCH] LinearClassifierMixin extended

---
 .../_mixins/linear_classifier_mixin.dart        | 17 +++++++++++------
 .../logistic_regressor_impl.dart                | 17 +----------------
 .../softmax_regressor_impl.dart                 | 17 +----------------
 .../predictor/assessable_predictor_mixin.dart   |  4 ++--
 4 files changed, 15 insertions(+), 40 deletions(-)

diff --git a/lib/src/classifier/_mixins/linear_classifier_mixin.dart b/lib/src/classifier/_mixins/linear_classifier_mixin.dart
index 21404e7a..a5d7cad3 100644
--- a/lib/src/classifier/_mixins/linear_classifier_mixin.dart
+++ b/lib/src/classifier/_mixins/linear_classifier_mixin.dart
@@ -3,10 +3,20 @@ import 'package:ml_algo/src/helpers/add_intercept_if.dart';
 import 'package:ml_algo/src/helpers/validate_coefficients_matrix.dart';
 import 'package:ml_algo/src/helpers/validate_test_features.dart';
 import 'package:ml_dataframe/ml_dataframe.dart';
+import 'package:ml_linalg/matrix.dart';
 
 mixin LinearClassifierMixin implements LinearClassifier {
   @override
   DataFrame predictProbabilities(DataFrame testFeatures) {
+    final probabilities = getProbabilitiesMatrix(testFeatures);
+
+    return DataFrame.fromMatrix(
+      probabilities,
+      header: classNames,
+    );
+  }
+
+  Matrix getProbabilitiesMatrix(DataFrame testFeatures) {
     validateTestFeatures(testFeatures, dtype);
 
     final processedFeatures = addInterceptIf(
@@ -18,12 +28,7 @@ mixin LinearClassifierMixin implements LinearClassifier {
     validateCoefficientsMatrix(coefficientsByClasses,
         processedFeatures.columnsNum);
 
-    final probabilities = linkFunction
+    return linkFunction
         .link(processedFeatures * coefficientsByClasses);
-
-    return DataFrame.fromMatrix(
-      probabilities,
-      header: classNames,
-    );
   }
 }
diff --git a/lib/src/classifier/logistic_regressor/logistic_regressor_impl.dart b/lib/src/classifier/logistic_regressor/logistic_regressor_impl.dart
index 4176f870..d5e02265 100644
--- a/lib/src/classifier/logistic_regressor/logistic_regressor_impl.dart
+++ b/lib/src/classifier/logistic_regressor/logistic_regressor_impl.dart
@@ -1,8 +1,6 @@
 import 'package:ml_algo/src/classifier/_mixins/linear_classifier_mixin.dart';
 import 'package:ml_algo/src/classifier/logistic_regressor/logistic_regressor.dart';
-import 'package:ml_algo/src/helpers/add_intercept_if.dart';
 import 'package:ml_algo/src/helpers/validate_coefficients_matrix.dart';
-import 'package:ml_algo/src/helpers/validate_test_features.dart';
 import 'package:ml_algo/src/link_function/link_function.dart';
 import 'package:ml_algo/src/predictor/assessable_predictor_mixin.dart';
 import 'package:ml_dataframe/ml_dataframe.dart';
@@ -62,20 +60,7 @@ class LogisticRegressorImpl with LinearClassifierMixin,
 
   @override
   DataFrame predict(DataFrame testFeatures) {
-    validateTestFeatures(testFeatures, dtype);
-
-    final processedFeatures = addInterceptIf(
-      fitIntercept,
-      testFeatures.toMatrix(dtype),
-      interceptScale,
-    );
-
-    validateCoefficientsMatrix(coefficientsByClasses,
-        processedFeatures.columnsNum);
-
-    final probabilities = linkFunction
-        .link(processedFeatures * coefficientsByClasses)
-        .getColumn(0);
+    final probabilities = getProbabilitiesMatrix(testFeatures).getColumn(0);
 
     final classesList = probabilities
         // TODO: use SIMD
diff --git a/lib/src/classifier/softmax_regressor/softmax_regressor_impl.dart b/lib/src/classifier/softmax_regressor/softmax_regressor_impl.dart
index 0e572e10..746e3421 100644
--- a/lib/src/classifier/softmax_regressor/softmax_regressor_impl.dart
+++ b/lib/src/classifier/softmax_regressor/softmax_regressor_impl.dart
@@ -1,8 +1,5 @@
 import 'package:ml_algo/src/classifier/_mixins/linear_classifier_mixin.dart';
 import 'package:ml_algo/src/classifier/softmax_regressor/softmax_regressor.dart';
-import 'package:ml_algo/src/helpers/add_intercept_if.dart';
-import 'package:ml_algo/src/helpers/validate_coefficients_matrix.dart';
-import 'package:ml_algo/src/helpers/validate_test_features.dart';
 import 'package:ml_algo/src/link_function/link_function.dart';
 import 'package:ml_algo/src/predictor/assessable_predictor_mixin.dart';
 import 'package:ml_dataframe/ml_dataframe.dart';
@@ -48,19 +45,7 @@ class SoftmaxRegressorImpl with LinearClassifierMixin,
 
   @override
   DataFrame predict(DataFrame testFeatures) {
-    validateTestFeatures(testFeatures, dtype);
-
-    final processedFeatures = addInterceptIf(
-      fitIntercept,
-      testFeatures.toMatrix(dtype),
-      interceptScale,
-    );
-
-    validateCoefficientsMatrix(coefficientsByClasses,
-        processedFeatures.columnsNum);
-
-    final allProbabilities = linkFunction
-        .link(processedFeatures * coefficientsByClasses);
+    final allProbabilities = getProbabilitiesMatrix(testFeatures);
 
     final classes = allProbabilities.mapRows((probabilities) {
       final positiveLabelIdx = probabilities
diff --git a/lib/src/predictor/assessable_predictor_mixin.dart b/lib/src/predictor/assessable_predictor_mixin.dart
index 8eeaf63d..3726aeff 100644
--- a/lib/src/predictor/assessable_predictor_mixin.dart
+++ b/lib/src/predictor/assessable_predictor_mixin.dart
@@ -15,8 +15,8 @@ mixin AssessablePredictorMixin implements Assessable, Predictor {
 
     final metric = MetricFactory.createByType(metricType);
     final prediction = predict(splits[0]);
-    final origLabels = splits[1].toMatrix();
+    final origLabels = splits[1].toMatrix(dtype);
 
-    return metric.getScore(prediction.toMatrix(), origLabels);
+    return metric.getScore(prediction.toMatrix(dtype), origLabels);
   }
 }