Merge branch 'master' of https://github.com/matthewgillett/MachineLearningSamples

Author: matthewgillett

README.md

@@ -17,11 +17,11 @@ How to get a stratified sample so the test and train datasets are sampled accros
 ### [Decision Tree with Categorical Feature in the DataSet](https://github.com/aosama/MachineLearningSamples/blob/master/src/main/scala/org/ibrahim/ezmachinelearning/DTShapeTypeWithCategoricalFeaturesExample.scala)
 How to index and encode categorical features.
 
-### [Decision Tree Multiple Categorical and Continuous Features in the DataSet](https://github.com/aosama/MachineLearningSamples/blob/master/src/main/scala/org/ibrahim/ezmachinelearning/DTCensusIncomeExample.scala.scala)
+### [Decision Tree Multiple Categorical and Continuous Features in the DataSet](https://github.com/aosama/MachineLearningSamples/blob/master/src/main/scala/org/ibrahim/ezmachinelearning/DTCensusIncomeExample.scala)
 How to handle multiple categorical and continuous features on a real-life data set.
 Uses the Census Income data set.
 
-### [Random Forest Multiple Categorical and Continuous Features in the DataSet](https://github.com/aosama/MachineLearningSamples/blob/master/src/main/scala/org/ibrahim/ezmachinelearning/RFCensusIncomeExample.scala.scala)
+### [Random Forest Multiple Categorical and Continuous Features in the DataSet](https://github.com/aosama/MachineLearningSamples/blob/master/src/main/scala/org/ibrahim/ezmachinelearning/RFCensusIncomeExample.scala)
 How to handle multiple categorical and continuous features on a real-life data set.
 Uses the Census Income data set.