Python MultinomialNB.predict_log_proba Examples

Example #1

File: test_allocator.py Project: rapidsai/cuml

def test_naive_bayes(nlp_20news):
    X, y = nlp_20news

    X = sparse_scipy_to_cp(X, cp.float32).astype(cp.float32)
    y = y.astype(cp.int32)

    with cupy_using_allocator(dummy_allocator):
        model = MultinomialNB()
        model.fit(X, y)

        y_hat = model.predict(X)
        y_hat = model.predict(X)
        y_hat = model.predict_proba(X)
        y_hat = model.predict_log_proba(X)
        y_hat = model.score(X, y)

        del y_hat

Example #2

File: test_naive_bayes.py Project: st071300/cuML

def test_predict_log_proba(x_dtype, y_dtype, nlp_20news):

    X, y = nlp_20news

    cu_X = sparse_scipy_to_cp(X, x_dtype).astype(x_dtype)
    cu_y = y.astype(y_dtype)

    cu_X = cu_X.tocsr()

    y = y.get()

    cuml_model = MultinomialNB()
    sk_model = skNB()

    cuml_model.fit(cu_X, cu_y)

    sk_model.fit(X, y)

    cuml_proba = cuml_model.predict_log_proba(cu_X).get()
    sk_proba = sk_model.predict_log_proba(X)

    assert_allclose(cuml_proba, sk_proba, atol=1e-2, rtol=1e-2)