random forest algorithm classifier

In this code we show you how to run random forest algorithm classifier in MATLAB :

Code:

TreeObject=TreeBagger(50,TrainData,class,'method ','classification','NVarToSample','all');
 

First parameter is the number of decision tree to use , TrainData is the training data vector , class is the label for each vector, method parameter is used to differ between regression and classification training. NVarToSample used to set the algorithm to "random forest" .

Now after training , how to use this object for classification :

Code:

[YFIT,scores] = predict(TreeObject,TestVector)

YFIT : label the high fitted class label.
scores : contain the score for each label .

_________________
M. S. Rakha, Ph.D.
Queen's University
Canada

Author: DrRakha
Mastermind

Posts: 2715
Have thanks: 74 time

Page 1 of 1

[ 1 post ]

Related Posts to : random forest algorithm classifier
Get the important variables of random forest classifier -
Cost Sensitive Classifier Random Forest Java in weka -
Random Search for tuning classifier parameters -
Random Forest Classification (Binary )- Supervised Learning -
KFold Cross-validation Random Forest Binary Classification -
Weka java code for Random Forest Cross Validation -
naive Bayes classifier in MATLAB -
Random to File -
php Random quote -
php Random image -

Topic Tags

Matlab Classifier

Powered by phpBB © 2000, 2002, 2005, 2007 phpBB Group
All copyrights reserved to codemiles.com 2007-2011
mileX v1.0 designed by codemiles team
Codemiles.com is a participant in the Amazon Services LLC Associates Program, an affiliate advertising program designed to provide a means for sites to earn advertising fees by advertising and linking to Amazon.com