Regression Systematic Error¶
Imports¶
[1]:
from deepchecks.base import Dataset
from sklearn.ensemble import GradientBoostingRegressor
from sklearn.datasets import load_diabetes
from sklearn.model_selection import train_test_split
from deepchecks.checks.performance import RegressionSystematicError
Generating data:¶
[2]:
diabetes_df = load_diabetes(return_X_y=False, as_frame=True).frame
train_df, test_df = train_test_split(diabetes_df, test_size=0.33, random_state=42)
train_df['target'] = train_df['target'] + 150
train = Dataset(train_df, label='target', cat_features=['sex'])
test = Dataset(test_df, label='target', cat_features=['sex'])
clf = GradientBoostingRegressor(random_state=0)
_ = clf.fit(train.data[train.features], train.data[train.label_name])
Running RegressionSystematicError check:¶
[3]:
check = RegressionSystematicError()
[4]:
check.run(test, clf)
Regression Systematic Error
Check the regression systematic error. Read More...
Additional Outputs
Non-zero mean of the error distribution indicated the presents of systematic error in model predictions