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decision-tree-with-py-libs
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fix

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Amir Hossein Moghiseh 2020-12-31 22:25:34 +03:30
parent ea2218b219
commit 77ea0c1ad0
1 changed files with 4 additions and 3 deletions
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app.py
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@ -8,7 +8,7 @@ from sklearn.metrics import classification_report
# Function importing Dataset # Function importing Dataset
def importdata(): def importdata():
dataset = pd.read_csv( 'Train.csv',sep= ',', header = None) dataset = pd.read_csv('Train.csv',sep= ',', header = None)
return dataset return dataset
# Function to split the dataset # Function to split the dataset
@ -16,7 +16,7 @@ def splitdataset(dataset):
# Separating the target variable # Separating the target variable
X = dataset.values[:, 1:5] X = dataset.values[:, 1:5]
Y = dataset.values[:, 0] Y = dataset.values[:,-1]
# Splitting the dataset into train and test # Splitting the dataset into train and test
X_train, X_test, y_train, y_test = train_test_split( X_train, X_test, y_train, y_test = train_test_split(
@ -74,7 +74,8 @@ def main():
# Building Phase # Building Phase
data = importdata() data = importdata()
X, Y, X_train, X_test, y_train, y_test = splitdataset(data) X, Y, X_train, X_test, y_train, y_test = splitdataset(data)
clf_gini = train_using_gini(X_train, X_test, y_train) clf_gini = train_using_gini(X_train, X_test, y_train)
clf_entropy = tarin_using_entropy(X_train, X_test, y_train) clf_entropy = tarin_using_entropy(X_train, X_test, y_train)