k fold splitter refactored

benchmark/cross_validator.dart

@@ -0,0 +1,44 @@
+// 10 sec
+import 'dart:async';
+
+import 'package:benchmark_harness/benchmark_harness.dart';
+import 'package:ml_algo/ml_algo.dart';
+import 'package:ml_linalg/matrix.dart';
+import 'package:ml_linalg/vector.dart';
+
+const observationsNum = 1000;
+const featuresNum = 20;
+
+class CrossValidatorBenchmark extends BenchmarkBase {
+  CrossValidatorBenchmark() : super('Cross validator benchmark');
+
+  Matrix features;
+  Matrix labels;
+  CrossValidator crossValidator;
+
+  static void main() {
+    CrossValidatorBenchmark().report();
+  }
+
+  @override
+  void run() {
+    crossValidator.evaluate((trainFeatures, trainLabels) =>
+        ParameterlessRegressor.knn(trainFeatures, trainLabels, k: 7),
+        features, labels, MetricType.mape);
+  }
+
+  @override
+  void setup() {
+    features = Matrix.fromRows(List.generate(observationsNum,
+            (i) => Vector.randomFilled(featuresNum)));
+    labels = Matrix.fromColumns([Vector.randomFilled(observationsNum)]);
+
+    crossValidator = CrossValidator.kFold(numberOfFolds: 5);
+  }
+
+  void tearDown() {}
+}
+
+Future main() async {
+  CrossValidatorBenchmark.main();
+}

lib/src/model_selection/cross_validator/cross_validator_impl.dart

@@ -30,9 +30,8 @@ class CrossValidatorImpl implements CrossValidator {
     }
 
     final allIndicesGroups = _splitter.split(observations.rowsNum);
-    // TODO get rid of length accessing
-    final scores = List<double>(allIndicesGroups.length);
-    int scoreCounter = 0;
+    var score = 0.0;
+    var folds = 0;
 
     for (final testIndices in allIndicesGroups) {
       final trainFeatures =
@@ -63,13 +62,14 @@ class CrossValidatorImpl implements CrossValidator {
         Matrix.fromRows(trainLabels, dtype: dtype),
       )..fit();
 
-      scores[scoreCounter++] = predictor.test(
+      score += predictor.test(
           Matrix.fromRows(testFeatures, dtype: dtype),
           Matrix.fromRows(testLabels, dtype: dtype),
           metric
       );
+      folds++;
     }
 
-    return scores.fold<double>(0, (sum, value) => sum + value) / scores.length;
+    return score / folds;
   }
 }

lib/src/model_selection/data_splitter/k_fold.dart

@@ -1,47 +1,28 @@
 import 'package:ml_algo/src/model_selection/data_splitter/splitter.dart';
+import 'package:xrange/zrange.dart';
 
 class KFoldSplitter implements Splitter {
-  final int _numberOfFolds;
-
   KFoldSplitter(this._numberOfFolds) {
     if (_numberOfFolds == 0 || _numberOfFolds == 1) {
       throw RangeError(
           'Number of folds must be greater than 1 and less than number of samples');
     }
   }
 
+  final int _numberOfFolds;
+
   @override
-  Iterable<Iterable<int>> split(int numberOfSamples) sync* {
-    if (_numberOfFolds > numberOfSamples) {
-      throw RangeError.range(_numberOfFolds, 0, numberOfSamples, null,
+  Iterable<Iterable<int>> split(int numOfObservations) sync* {
+    if (_numberOfFolds > numOfObservations) {
+      throw RangeError.range(_numberOfFolds, 0, numOfObservations, null,
           'Number of folds must be less than number of samples!');
     }
-
-    final remainder = numberOfSamples % _numberOfFolds;
-    final size = (numberOfSamples / _numberOfFolds).truncate();
-    final sizes = List<int>.filled(_numberOfFolds, 1)
-        .map((int el) => el * size)
-        .toList(growable: false);
-
-    if (remainder > 0) {
-      final range =
-          sizes.take(remainder).map((int el) => ++el).toList(growable: false);
-      sizes.setRange(0, remainder, range);
-    }
-
-    int startIdx = 0;
-    int endIdx = 0;
-
-    for (int i = 0; i < sizes.length; i++) {
-      endIdx = startIdx + sizes[i];
-      yield _range(startIdx, endIdx);
+    final remainder = numOfObservations % _numberOfFolds;
+    final foldSize = numOfObservations ~/ _numberOfFolds;
+    for (int i = 0, startIdx = 0, endIdx = 0; i < _numberOfFolds; i++) {
+      endIdx = startIdx + foldSize + (i >= _numberOfFolds - remainder ? 1 : 0);
+      yield ZRange.closedOpen(startIdx, endIdx).values();
       startIdx = endIdx;
     }
   }
-
-  Iterable<int> _range(int start, int end) sync* {
-    for (int i = start; i < end; i++) {
-      yield i;
-    }
-  }
 }

test/data_splitter/data_splitter_test.dart

@@ -16,11 +16,11 @@ void main() {
       expect(
           kfoldSplitter.split(12),
           equals([
-            [0, 1, 2],
-            [3, 4, 5],
-            [6, 7],
-            [8, 9],
-            [10, 11]
+            [0, 1],
+            [2, 3],
+            [4, 5],
+            [6, 7, 8],
+            [9, 10, 11],
           ]));
 
       kfoldSplitter = KFoldSplitter(4);
@@ -64,11 +64,11 @@ void main() {
       expect(
           kfoldSplitter.split(37),
           equals([
-            [0, 1, 2, 3, 4, 5, 6, 7],
-            [8, 9, 10, 11, 12, 13, 14, 15],
-            [16, 17, 18, 19, 20, 21, 22],
-            [23, 24, 25, 26, 27, 28, 29],
-            [30, 31, 32, 33, 34, 35, 36]
+            [0, 1, 2, 3, 4, 5, 6],
+            [7, 8, 9, 10, 11, 12, 13],
+            [14, 15, 16, 17, 18, 19, 20],
+            [21, 22, 23, 24, 25, 26, 27, 28],
+            [29, 30, 31, 32, 33, 34, 35, 36],
           ]));
 
       kfoldSplitter = KFoldSplitter(3);