Invalid parameter for sklearn estimator pipeline

Question

I am implementing an example from the O'Reilly book "Introduction to Machine Learning with Python", using Python 2.7 and sklearn 0.16.

The code I am using:

pipe = make_pipeline(TfidfVectorizer(), LogisticRegression())
param_grid = {"logisticregression_C": [0.001, 0.01, 0.1, 1, 10, 100], "tfidfvectorizer_ngram_range": [(1,1), (1,2), (1,3)]}
grid = GridSearchCV(pipe, param_grid, cv=5)
grid.fit(X_train, y_train)
print("Best cross-validation score: {:.2f}".format(grid.best_score_))

The error being returned boils down to:

ValueError: Invalid parameter logisticregression_C for estimator Pipeline

Is this an error related to using Make_pipeline from v.0.16? What is causing this error?

Answer 1

There should be two underscores between estimator name and it's parameters in a Pipeline logisticregression__C. Do the same for tfidfvectorizer

See the example at http://scikit-learn.org/stable/auto_examples/plot_compare_reduction.html#sphx-glr-auto-examples-plot-compare-reduction-py