"ml_linalg" 13.11.15 used (#248)

Author: gyrdym

CHANGELOG.md

@@ -1,5 +1,8 @@
 # Changelog
 
+## 16.17.7
+- ml_linalg ^13.11.15 used
+
 ## 16.17.6
 - ml_linalg version fixed (13.11.11)
 - benchmark info added

benchmark/sgd_regressor.dart

@@ -1,3 +1,5 @@
+// Approx. 3.0 second (MacBook Pro 2019, Dart version: 2.16.0)
+
 import 'package:benchmark_harness/benchmark_harness.dart';
 import 'package:ml_algo/ml_algo.dart';
 import 'package:ml_dataframe/ml_dataframe.dart';
@@ -24,9 +26,10 @@ class SGDRegressorBenchmark extends BenchmarkBase {
   @override
   void setup() {
     final features = Matrix.fromRows(List.generate(
-        observationsNum, (i) => Vector.randomFilled(featuresNum)));
+        observationsNum, (i) => Vector.randomFilled(featuresNum, seed: 23)));
 
-    final labels = Matrix.fromColumns([Vector.randomFilled(observationsNum)]);
+    final labels =
+        Matrix.fromColumns([Vector.randomFilled(observationsNum, seed: 25)]);
 
     trainData = DataFrame.fromMatrix(
       Matrix.fromColumns([

e2e/decision_tree_classifier/iris_tree.svg

@@ -1,3 +1,3 @@
 #!/bin/bash
 
-pub run test e2e -p vm
+dart test e2e -p vm

e2e/decision_tree_classifier/pima_indians_tree.svg

@@ -2,7 +2,7 @@ import 'package:ml_algo/ml_algo.dart';
 import 'package:ml_dataframe/ml_dataframe.dart';
 
 void main() {
-  final samples = getPimaIndiansDiabetesDataFrame().shuffle();
+  final samples = getPimaIndiansDiabetesDataFrame().shuffle(seed: 4);
   final splits = splitData(samples, [0.8]);
   final model = LogisticRegressor(
     splits.first,

e2e_tests.sh

@@ -1,6 +1,6 @@
 name: ml_algo
 description: Machine learning algorithms, Machine learning models performance evaluation functionality
-version: 16.17.6
+version: 16.17.7
 homepage: https://github.com/gyrdym/ml_algo
 
 environment:
@@ -11,7 +11,7 @@ dependencies:
   injector: ^2.0.0
   json_annotation: ^4.0.0
   ml_dataframe: ^1.6.0
-  ml_linalg: 13.11.11
+  ml_linalg: ^13.11.15
   ml_preprocessing: ^7.0.2
   quiver: ^3.0.0
   xrange: ^2.0.0