Savable Classifier

savable_classifier.py

import uuid
from pathlib import Path

from sklearn.base import BaseEstimator, ClassifierMixin, clone
from sklearn.datasets import make_classification
from sklearn.externals import joblib
from sklearn.feature_selection import SelectPercentile
from sklearn.model_selection import cross_val_score
from sklearn.pipeline import make_pipeline
from sklearn.svm import LinearSVC


class SavableClassifier(BaseEstimator, ClassifierMixin):
    def __init__(self, estimator, export_directory):
        self.estimator = estimator
        self.export_directory = export_directory

    def fit(self, X, y):
        self.estimator_ = clone(self.estimator).fit(X, y)
        self._save()
        return self

    def predict(self, X):
        return self.estimator_.predict(X)

    def _save(self):
        filename = "{}.pkl".format(uuid.uuid4().hex)
        fullpath = Path(self.export_directory, filename)
        joblib.dump(self.estimator_, fullpath)


X, y = make_classification(random_state=0)

model = make_pipeline(
    SelectPercentile(percentile=0.5),
    LinearSVC()
)


sc = SavableClassifier(model, "/temp")

if __name__ == '__main__':
    cross_val_score(sc, X, y, cv=10, n_jobs=1)