smile.classification

Enum DiscreteNaiveBayes.Model

java.lang.Object

java.lang.Enum<DiscreteNaiveBayes.Model>

smile.classification.DiscreteNaiveBayes.Model

All Implemented Interfaces:

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

Enclosing class:

DiscreteNaiveBayes

public static enum DiscreteNaiveBayes.Model
extends java.lang.Enum<DiscreteNaiveBayes.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.
CNB Complement Naive Bayes.
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.
TWCNB Transformed Weight-normalized Complement Naive Bayes.
WCNB Weight-normalized Complement Naive Bayes.

Method Summary

Modifier and Type	Method and Description
static DiscreteNaiveBayes.Model	valueOf(java.lang.String name) Returns the enum constant of this type with the specified name.
static DiscreteNaiveBayes.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

MULTINOMIAL

public static final DiscreteNaiveBayes.Model MULTINOMIAL

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

BERNOULLI

public static final DiscreteNaiveBayes.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 DiscreteNaiveBayes.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.

CNB

public static final DiscreteNaiveBayes.Model CNB

Complement Naive Bayes. To deal with skewed training data, CNB estimates parameters of a class c using data from all classes except c. CNB’s estimates may be more effective because each uses a more even amount of training data per class, which will lessen the bias in the weight estimates.

WCNB

public static final DiscreteNaiveBayes.Model WCNB

Weight-normalized Complement Naive Bayes. In practice, it is often the case that weights tend to lean toward one class or the other. When the magnitude of Naive Bayes’ weight vector is larger in one class than the others, the larger magnitude class may be preferred. To correct for the fact that some classes have greater dependencies, WCNB normalizes the weight vectors.

TWCNB

public static final DiscreteNaiveBayes.Model TWCNB

Transformed Weight-normalized Complement Naive Bayes. Before feeding into WCNB, TWCNB transforms term frequencies including TF transform, IDF transform, and length normalization. Because of IDF, TWCNB supports only batch mode.

Method Detail

values

public static DiscreteNaiveBayes.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 (DiscreteNaiveBayes.Model c : DiscreteNaiveBayes.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 DiscreteNaiveBayes.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