def run_error_analyzer_on_models(X_train,
y_train,
X_test,
y_test,
feature_names,
model_task,
filters=None,
composite_filters=None,
matrix_features=None,
quantile_binning=False,
num_bins=BIN_THRESHOLD,
metric=None):
if model_task == ModelTask.CLASSIFICATION:
models = create_models_classification(X_train, y_train)
else:
models = create_models_regression(X_train, y_train)
for model in models:
categorical_features = []
run_error_analyzer(model,
X_test,
y_test,
feature_names,
categorical_features,
model_task=model_task,
filters=filters,
composite_filters=composite_filters,
matrix_features=matrix_features,
quantile_binning=quantile_binning,
num_bins=num_bins,
metric=metric)
def run_error_analyzer_on_models(X_train,
y_train,
X_test,
y_test,
feature_names,
model_task,
filters=None,
composite_filters=None,
matrix_features=None):
if model_task == ModelTask.CLASSIFICATION:
models = create_models_classification(X_train, y_train)
else:
models = create_models_regression(X_train, y_train)
for model in models:
categorical_features = []
run_error_analyzer(model,
X_test,
y_test,
feature_names,
categorical_features,
model_task=model_task,
filters=filters,
composite_filters=composite_filters,
matrix_features=matrix_features)
def test_error_report_housing(self):
X_train, X_test, y_train, y_test, feature_names = \
create_housing_data()
models = create_models_regression(X_train, y_train)
for model in models:
categorical_features = []
run_error_analyzer(model, X_test, y_test, feature_names,
categorical_features)
def test_importances_boston(self):
X_train, X_test, y_train, y_test, feature_names = \
create_boston_data()
models = create_models_regression(X_train, y_train)
for model in models:
categorical_features = []
run_error_analyzer(model, X_test, y_test, feature_names,
categorical_features)
def test_modelanalysis_boston(self, manager_type):
x_train, x_test, y_train, y_test, feature_names = \
create_boston_data()
x_train = pd.DataFrame(x_train, columns=feature_names)
x_test = pd.DataFrame(x_test, columns=feature_names)
models = create_models_regression(x_train, y_train)
x_train[LABELS] = y_train
x_test[LABELS] = y_test
manager_args = {DESIRED_RANGE: [10, 20]}
for model in models:
run_model_analysis(model, x_train, x_test, LABELS, ['RM'],
manager_type, manager_args)
def test_error_report_housing_pandas(self, filter_features):
X_train, X_test, y_train, y_test, feature_names = \
create_housing_data()
X_train = create_dataframe(X_train, feature_names)
X_test = create_dataframe(X_test, feature_names)
models = create_models_regression(X_train, y_train)
for model in models:
categorical_features = []
run_error_analyzer(model,
X_test,
y_test,
feature_names,
categorical_features,
filter_features=filter_features)