Metrics: documentation for MAPE metric extended

CHANGELOG.md

@@ -1,5 +1,8 @@
 # Changelog
 
+## 15.2.2
+- Documentation for MAPE metrics improved
+
 ## 15.2.1
 - `classificationMetrics` constant list added
 - `regressionMetrics` constant list added

lib/src/metric/metric_type.dart

@@ -1,11 +1,19 @@
 /// Metrics for measuring the quality of the prediction.
 enum MetricType {
-  /// Mean percentage absolute error (MAPE), a regression metric. The less the
-  /// score produced by the metric, the better the prediction's quality is. Can
-  /// lead to error if there are zero values among the original values. Normally,
-  /// the metric produces scores within the range [0, 1], but extremely high
-  /// predicted values (>> original values) can produce scores which are
-  /// greater than 1.
+  /// Mean percentage absolute error (MAPE), a regression metric. The formula
+  /// is:
+  ///
+  ///
+  /// ![{\mbox{Score}}={\frac{1}{n}}\sum_{{t=1}}^{n}\left|{\frac{Y_{t}-\widehat{Y}_{t}}{Y_{t}}}\right|](https://latex.codecogs.com/gif.latex?%7B%5Cmbox%7BScore%7D%7D%3D%7B%5Cfrac%7B1%7D%7Bn%7D%7D%5Csum_%7B%7Bt%3D1%7D%7D%5E%7Bn%7D%5Cleft%7C%7B%5Cfrac%7BY_%7Bt%7D-%5Cwidehat%7BY%7D_%7Bt%7D%7D%7BY_%7Bt%7D%7D%7D%5Cright%7C)
+  ///
+  ///
+  /// where Y - original value, Y with hat - predicted one
+  ///
+  /// The less the score produced by the metric, the better the prediction's
+  /// quality is. Can lead to error if there are zero values among the original
+  /// values. Normally, the metric produces scores within the range [0, 1]
+  /// (both included), but extremely high predicted values (>> original values)
+  /// can produce scores which are greater than 1.
   mape,
 
   /// Root mean squared error, a regression metric. The less the score produced

pubspec.yaml

@@ -1,6 +1,6 @@
 name: ml_algo
 description: Machine learning algorithms, Machine learning models performance evaluation functionality
-version: 15.2.1
+version: 15.2.2
 homepage: https://github.com/gyrdym/ml_algo
 
 environment: