Add Naive Bayes

[param087]

1. Bernoulli Naive Bayes Classifier -

• BernoullilNB( alpha:1.0) -

  • alpha(Float) - Smoothing parameter.

  API Methods -

  • fit(data: , labels: ) - Fit naive bayes classifier.
  • prediction(for: ) - Perform classification on input data.
  • predictLogProba(data: ) - Returns log probability of input data.
  • score(data: , labels: ) - Returns the mean accuracy.

  References

  • https://en.wikipedia.org/wiki/Naive_Bayes_classifier
  • https://scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.BernoulliNB.html
  • https://nlp.stanford.edu/IR-book/html/htmledition/the-bernoulli-model-1.html

2. Multinomial Naive Bayes Classifier -

• MultinomialNB( alpha:1.0) -

  • alpha(Float) - Smoothing parameter.

  API Methods -

  • fit(data: , labels: ) - Fit naive bayes classifier
  • prediction(for: ) - Perform classification on data.
  • predictLogProba(data: ) - Returns log probability of data.
  • score(data: , labels: ) - Returns the mean accuracy.

  References

  • https://en.wikipedia.org/wiki/Naive_Bayes_classifier
  • https://scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.MultinomialNB.htmll
  • https://nlp.stanford.edu/IR-book/html/htmledition/naive-bayes-text-classification-1.html

  3. Gaussian Naive Bayes Classifier -

  • GaussianNB( ) -

  API Methods -

  • fit(data: , labels: ) - Fit naive bayes classifier
  • prediction(for: ) - Perform classification on data.
  • prob(data: ) - Return gaussian probability in log.
  • predictLogProba(data: ) - Returns log probability of data.
  • score(data: ,labels: ) - Returns the mean accuracy.

  References

  • https://en.wikipedia.org/wiki/Naive_Bayes_classifier
  • https://scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.GaussianNB.html