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]