model.fit(X_train, y_train)
print("Test")
eval_metric(confusion_matrix(y_test, model.predict(X_test).round()))
print("Training")
eval_metric(confusion_matrix(y_train, model.predict(X_train).round()))
print("Decision tree classifier")
model = DecisionTreeClassifier(max_depth=None, min_samples_split=2)
model.fit(X_train, y_train)
print("Test")
eval_metric(confusion_matrix(y_test, model.predict(X_test).round()))
print("Training")
eval_metric(confusion_matrix(y_train, model.predict(X_train).round()))
print("Decision tree classifier with scaler and PCA")
model = make_pipeline(
StandardScaler(), PCA(n_components=7),
ExtraTreesClassifier(n_estimators=225,
max_depth=None,
min_samples_split=2))
model.fit(X_train, y_train)
print("Test")
eval_metric(confusion_matrix(y_test, model.predict(X_test).round()))
print("Training")
eval_metric(confusion_matrix(y_train, model.predict(X_train).round()))
print("Architecture ANN search")
from Kaggle.ANN_constructor.ANNArchitectureGridSearch import architecture_grid_search, architecture_random_grid_search
architecture_random_grid_search(X_train, y_train, X_test, y_test)
architecture_grid_search(X_train, y_train, X_test, y_test)
print("Decision tree classifier")
model = DecisionTreeClassifier(max_depth=None, min_samples_split=2)
model.fit(X_train, y_train)
print("Test")
eval_metric(confusion_matrix(y_test, model.predict(X_test).round()))
print("Training")
eval_metric(confusion_matrix(y_train, model.predict(X_train).round()))
print("Decision tree classifier with scaler and PCA")
model = make_pipeline(
StandardScaler(), PCA(n_components=4),
ExtraTreesClassifier(n_estimators=100,
max_depth=None,
min_samples_split=2))
model.fit(X_train, y_train)
print("Test")
eval_metric(confusion_matrix(y_test, model.predict(X_test).round()))
print("Training")
eval_metric(confusion_matrix(y_train, model.predict(X_train).round()))
print("Architecture ANN search")
from Kaggle.ANN_constructor.ANNArchitectureGridSearch import architecture_grid_search, architecture_random_grid_search
#architecture_random_grid_search(X_train, y_train, X_test, y_test)
architecture_grid_search(X_train,
y_train,
X_test,
y_test,
max_width=12,
max_depth=10)