How to use 'syntax to import decision tree classifier in sklearn' in Python

Every line of 'syntax to import decision tree classifier in sklearn' code snippets is scanned for vulnerabilities by our powerful machine learning engine that combs millions of open source libraries, ensuring your Python code is secure.

All examples are scanned by Snyk Code

By copying the Snyk Code Snippets you agree to
this disclaimer
14def get_fast_classifiers(n_classes):
15 """Get a list of very fast classifiers.
16
17 Parameters
18 ----------
19 n_classes : int
20 Number of classes in the dataset. Used to decide on the complexity
21 of some of the classifiers.
22
23
24 Returns
25 -------
26 fast_classifiers : list of sklearn estimators
27 List of classification models that can be fitted and evaluated very
28 quickly.
29 """
30 return [
31 # These are sorted by approximate speed
32 DummyClassifier(strategy="prior"),
33 GaussianNB(),
34 make_pipeline(MinMaxScaler(), MultinomialNB()),
35 DecisionTreeClassifier(max_depth=1, class_weight="balanced"),
36 DecisionTreeClassifier(max_depth=max(5, n_classes),
37 class_weight="balanced"),
38 DecisionTreeClassifier(class_weight="balanced",
39 min_impurity_decrease=.01),
40 LogisticRegression(C=.1, solver='lbfgs', multi_class='auto',
41 class_weight='balanced', max_iter=1000),
42 # FIXME Add warm starting here?
43 LogisticRegression(C=1, solver='lbfgs', multi_class='auto',
44 class_weight='balanced', max_iter=1000)
45 ]
Important

Use secure code every time

Secure your code as it's written. Use Snyk Code to scan source code in minutes – no build needed – and fix issues immediately. Enable Snyk Code

332def test_export_to_sklearn_pipeline(self):
333 from lale.lib.sklearn import PCA
334 from lale.lib.sklearn import KNeighborsClassifier
335 from sklearn.pipeline import make_pipeline
336 lale_pipeline = PCA(n_components=3) >> KNeighborsClassifier()
337 trained_lale_pipeline = lale_pipeline.fit(self.X_train, self.y_train)
338 sklearn_pipeline = trained_lale_pipeline.export_to_sklearn_pipeline()
339 for i, pipeline_step in enumerate(sklearn_pipeline.named_steps):
340 sklearn_step_params = sklearn_pipeline.named_steps[pipeline_step].get_params()
341 lale_sklearn_params = trained_lale_pipeline.steps()[i]._impl._wrapped_model.get_params()
342 self.assertEqual(sklearn_step_params, lale_sklearn_params)
343 self.assert_equal_predictions(sklearn_pipeline, trained_lale_pipeline)

Related snippets