smile.classification

Enum NaiveBayes.Model

java.lang.Object

java.lang.Enum<NaiveBayes.Model>

smile.classification.NaiveBayes.Model

All Implemented Interfaces:

java.io.Serializable, java.lang.Comparable<NaiveBayes.Model>

Enclosing class:

NaiveBayes

public static enum NaiveBayes.Model
extends java.lang.Enum<NaiveBayes.Model>

The generation models of naive Bayes classifier. For document classification in NLP, there are two different ways we can set up an naive Bayes classifier: multinomial model and Bernoulli model. The multinomial model generates one term from the vocabulary in each position of the document. The multivariate Bernoulli model or Bernoulli model generates an indicator for each term of the vocabulary, either indicating presence of the term in the document or indicating absence.

Enum Constant Summary

Enum Constants

Enum Constant and Description
BERNOULLI The document Bernoulli model generates an indicator for each term of the vocabulary, either indicating presence of the term in the document or indicating absence.
GENERAL The general model is for a set of independent variables with any kind of underlying distributions.
MULTINOMIAL The document multinomial model generates one term from the vocabulary in each position of the document.
POLYAURN The document Polya Urn model is similar to MULTINOMIAL but different in the conditional probability update during learning.

Method Summary

Modifier and Type	Method and Description
static NaiveBayes.Model	valueOf(java.lang.String name) Returns the enum constant of this type with the specified name.
static NaiveBayes.Model[]	values() Returns an array containing the constants of this enum type, in the order they are declared.

Methods inherited from class java.lang.Enum

clone, compareTo, equals, finalize, getDeclaringClass, hashCode, name, ordinal, toString, valueOf

Methods inherited from class java.lang.Object

getClass, notify, notifyAll, wait, wait, wait

Enum Constant Detail

GENERAL

public static final NaiveBayes.Model GENERAL

The general model is for a set of independent variables with any kind of underlying distributions. The users have to provide estimated distribution for each independent variables.

MULTINOMIAL

public static final NaiveBayes.Model MULTINOMIAL

The document multinomial model generates one term from the vocabulary in each position of the document.

BERNOULLI

public static final NaiveBayes.Model BERNOULLI

The document Bernoulli model generates an indicator for each term of the vocabulary, either indicating presence of the term in the document or indicating absence.

POLYAURN

public static final NaiveBayes.Model POLYAURN

The document Polya Urn model is similar to MULTINOMIAL but different in the conditional probability update during learning. It simply add twice for what is seen in training data instead of one time.

Method Detail

values

public static NaiveBayes.Model[] values()

Returns an array containing the constants of this enum type, in the order they are declared. This method may be used to iterate over the constants as follows:

for (NaiveBayes.Model c : NaiveBayes.Model.values())
    System.out.println(c);

Returns:

an array containing the constants of this enum type, in the order they are declared

valueOf

public static NaiveBayes.Model valueOf(java.lang.String name)

Returns the enum constant of this type with the specified name. The string must match exactly an identifier used to declare an enum constant in this type. (Extraneous whitespace characters are not permitted.)

Parameters:

name - the name of the enum constant to be returned.

Returns:

the enum constant with the specified name

Throws:

java.lang.IllegalArgumentException - if this enum type has no constant with the specified name

java.lang.NullPointerException - if the argument is null