Updated the documentation.

Author: Olcay Taner YILDIZ

Classification/Classifier/Bagging.py

@@ -35,4 +35,8 @@ def train(self,
         self.model = TreeEnsembleModel(forest)
 
     def loadModel(self, fileName: str):
+        """
+        Loads the Bagging ensemble model from an input file.
+        :param fileName: File name of the decision tree model.
+        """
         self.model = TreeEnsembleModel(fileName)

Classification/Classifier/C45.py

@@ -34,4 +34,8 @@ def train(self,
         self.model = tree
 
     def loadModel(self, fileName: str):
+        """
+        Loads the decision tree model from an input file.
+        :param fileName: File name of the decision tree model.
+        """
         self.model = DecisionTree(fileName)

Classification/Classifier/C45Stump.py

@@ -24,4 +24,8 @@ def train(self,
                                                isStump=True))
 
     def loadModel(self, fileName: str):
+        """
+        Loads the decision tree model from an input file.
+        :param fileName: File name of the decision tree model.
+        """
         self.model = DecisionTree(fileName)

Classification/Classifier/DeepNetwork.py

@@ -29,4 +29,8 @@ def train(self,
                                       parameters=parameters)
 
     def loadModel(self, fileName: str):
+        """
+        Loads the deep network model from an input file.
+        :param fileName: File name of the deep network model.
+        """
         self.model = DeepNetworkModel(fileName)

Classification/Classifier/Dummy.py

@@ -23,4 +23,8 @@ def train(self,
         self.model = DummyModel(trainSet)
 
     def loadModel(self, fileName: str):
+        """
+        Loads the dummy model from an input file.
+        :param fileName: File name of the dummy model.
+        """
         self.model = DummyModel(fileName)

Classification/Classifier/KMeans.py

@@ -10,6 +10,11 @@ class KMeans(Classifier):
     def train(self,
               trainSet: InstanceList,
               parameters: KMeansParameter):
+        """
+        Training algorithm for K-Means classifier. K-Means finds the mean of each class for training.
+        :param trainSet: Training data given to the algorithm.
+        :param parameters: distance metric used to calculate the distance between two instances.
+        """
         prior_distribution = trainSet.classDistribution()
         class_means = InstanceList()
         class_lists = Partition(trainSet)
@@ -20,4 +25,8 @@ def train(self,
                                  distanceMetric=parameters.getDistanceMetric())
 
     def loadModel(self, fileName: str):
+        """
+        Loads the K-means model from an input file.
+        :param fileName: File name of the K-means model.
+        """
         self.model = KMeansModel(fileName)

Classification/Classifier/Knn.py

@@ -24,4 +24,8 @@ def train(self,
                               distanceMetric=parameters.getDistanceMetric())
 
     def loadModel(self, fileName: str):
+        """
+        Loads the K-nearest neighbor model from an input file.
+        :param fileName: File name of the K-nearest neighbor model.
+        """
         self.model = KnnModel(fileName)

Classification/Classifier/Lda.py

@@ -48,4 +48,8 @@ def train(self,
         self.model = LdaModel(prior_distribution, w, w0)
 
     def loadModel(self, fileName: str):
+        """
+        Loads the Lda model from an input file.
+        :param fileName: File name of the Lda model.
+        """
         self.model = LdaModel(fileName)

Classification/Classifier/LinearPerceptron.py

@@ -31,4 +31,8 @@ def train(self,
                                            parameters=parameters)
 
     def loadModel(self, fileName: str):
+        """
+        Loads the linear perceptron model from an input file.
+        :param fileName: File name of the linear perceptron model.
+        """
         self.model = LinearPerceptronModel(fileName)

Classification/Classifier/MultiLayerPerceptron.py

@@ -31,4 +31,8 @@ def train(self,
                                                parameters=parameters)
 
     def loadModel(self, fileName: str):
+        """
+        Loads the multi-layer perceptron model from an input file.
+        :param fileName: File name of the multi-layer perceptron model.
+        """
         self.model = MultiLayerPerceptronModel(fileName)