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sklearn.naive_bayes

sklearn.naive_bayes.MultinomialNB

  • sklearn.naive_bayes.MultinomialNB

This class provides Naive Bayes classifier for multinomial models with distributed large-scale learning.

Methods

sklearn.naive_bayes.MultinomialNB.fit

  • sklearn.naive_bayes.MultinomialNB.fit(X, y, sample_weight=None)

    Supported Arguments


    - X: NumPy Array or Pandas Dataframes. - y: NumPy Array or Pandas Dataframes.

sklearn.naive_bayes.MultinomialNB.predict

  • sklearn.naive_bayes.MultinomialNB.predict(X)

    Supported Arguments


    - X: NumPy Array or Pandas Dataframes.

sklearn.naive_bayes.MultinomialNB.score

  • sklearn.naive_bayes.MultinomialNB.score(X, y, sample_weight=None)

    Supported Arguments


    - X: NumPy Array or Pandas Dataframes. - y: NumPy Array or Pandas Dataframes. - sample_weight: Numeric NumPy Array or Pandas Dataframes.

Example Usage

>>> import bodo
>>> import numpy as np
>>> from sklearn.naive_bayes import MultinomialNB
>>> rng = np.random.RandomState(1)
>>> X = rng.randint(5, size=(6, 100))
>>> y = np.array([1, 2, 3, 4, 5, 6])
>>> X_test = rng.randint(5, size=(1, 100))
>>> @bodo.jit
... def test_mnb(X, y, X_test):
...   clf = MultinomialNB()
...   clf.fit(X, y)
...   ans = clf.predict(X_test)
...   print(ans)
...
>>> test_mnb(X, y, X_test)
[5]