MACHINE LEARNING with MATLAB. SUPERVISED LEARNING and CLASSIFICATION by J. Smith

Author:J. Smith [Smith, J.]
Language: eng
Format: azw3
Publisher: UNKNOWN
Published: 2017-04-10T04:00:00+00:00

4.2 Functions

fitcnb

Train multiclass naive Bayes model

predict

Predict labels using naive Bayes classification model

templateNaiveBayes

Naive Bayes classifier template

4.2.1 fitcnb

Train multiclass naive Bayes model

Syntax

Mdl = fitcnb(Tbl,ResponseVarName)

Mdl = fitcnb(Tbl,formula)

Mdl = fitcnb(Tbl,Y)

Mdl = fitcnb(X,Y)

Mdl = fitcnb(___,Name,Value)

Description

Mdl = fitcnb(Tbl,ResponseVarName) returns a multiclass naive Bayes model (Mdl), trained by the predictors in table Tbl and class labels in the variable Tbl.ResponseVarName.

Mdl = fitcnb(Tbl,formula) returns a multiclass naive Bayes model (Mdl), trained by the predictors in table Tbl. formula is an explanatory model of the response and a subset of predictor variables in Tbl used to fit Mdl.

Mdl = fitcnb(Tbl,Y) returns a multiclass naive Bayes model (Mdl), trained by the predictors in the table Tbl and class labels in the array Y.

Mdl = fitcnb(X,Y) returns a multiclass naive Bayes model (Mdl), trained by predictors X and class labels Y.

Mdl = fitcnb(___,Name,Value) returns a naive Bayes classifier with additional options specified by one or more Name,Value pair arguments, using any of the previous syntaxes. For example, you can specify a distribution to model the data, prior probabilities for the classes, or the kernel smoothing window bandwidth.

Examples

Download

Copyright Disclaimer:
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.