sklearn_compat_custom_estimator_wrapper_quickstart.py

1from sklearn.base import BaseEstimator, ClassifierMixin
2from sklearn_compat.postprocessing import GenericEstimator
3
4class MyEstimator(BaseEstimator, ClassifierMixin):
5    def __init__(self, param1=1, param2=2):
6        self.param1 = param1
7        self.param2 = param2
8
9    def fit(self, X, y):
10        # Your fitting logic here
11        self.is_fitted_ = True
12        return self
13
14    def predict(self, X):
15        # Your prediction logic here
16        return [0] * len(X)
17
18# Usage of sklearn-compat to wrap the estimator
19# This ensures it behaves consistently across sklearn versions
20est = MyEstimator()
21compat_est = GenericEstimator(est)
22
23# Now compat_est can be used in pipelines or grid searches
24# with better compatibility guarantees.