def __AppendTree(self):
num_rows = self.df.shape[0]
bootstraps = np.random.randint(0,num_rows, num_rows); # get random rows with replacement
df_boot = self.df.iloc[bootstraps,:] # actually get the rows
currTree = DecisionTree()
CompleteDataSet = self.df
if self.CompleteDataSet is not None:
CompleteDataSet = self.CompleteDataSet
currTree.BuildFromDataFrame(df_boot, num_rows, 2, None, self.__HandleUnknowns, CompleteDataSet)
self.trees.append(currTree)
def __AddNewTree(self):
df = self.df
currTree = DecisionTree()
currTree.BuildFromDataFrame(df, 1, 2, self.D, self.HandleUnknowns)
predictions = self.__GetPredictions(df, currTree)
error = self.__CalculateTreeError(df, predictions)
# print(error)
alpha = self.__CalculateAlpha(error)
self.alphas.append(alpha)
# print(self.D)
self.__UpdateD(df, predictions, alpha)
# print(self.D)
self.trees.append(currTree)