updated CHANGELOG.md

CHANGELOG.md

@@ -13,19 +13,20 @@ From v3.1.1 to v3.2.0
 
 ## New Features
 
-- Added a range of new metrics: `BEDROC`, `EnrichmentFactor`, `RobustInitialEnhancement`,
+- Added a range of new
+  metrics: `BEDROC`, `EnrichmentFactor`, `RobustInitialEnhancement`,
   `Prevalence`, `Sensitivity`, `Specificity`, `PositivePredictivity`, `NegativePredictivity`,
-   `CohenKappa`, `BalancedPositivePredictivity`, `BalancedNegativePredictivity`,
-   `BalancedMatthewsCorrcoeff`, `BalancedCohenKappa`, `KSlope`, `R20`, `KPrimeSlope`,
-   `RPrime20`, `Pearson`, `Spearman`, `Kendall`, `AverageFoldError`, 
-   `AbsoluteAverageFoldError`, `PercentageWithinFoldError`
+  `CohenKappa`, `BalancedPositivePredictivity`, `BalancedNegativePredictivity`,
+  `BalancedMatthewsCorrcoeff`, `BalancedCohenKappa`, `KSlope`, `R20`, `KPrimeSlope`,
+  `RPrime20`, `Pearson`, `Spearman`, `Kendall`, `AverageFoldError`,
+  `AbsoluteAverageFoldError`, `PercentageWithinFoldError`
 - Added `MaskedMetric` which can be wrapped around any metric to mask datapoints
   when a target value is missing.
 - Added a tutorial on model and data serialization.
 - `ApplicabilityDomain` now has a `transform` method that can be used to transform
   a dataset to a continuous applicability domain score, such as the distance to the
-  nearest neighbor in the training set (an example is added in the 
-  `tutorials.basics.data.applicability_domain.ipynb` tutorial).
+  nearest neighbor in the training set (an example was added to the
+  [tutorials](./tutorials/basics/data/applicability_domain.ipynb)).
 
 ## Removed Features