How do I include multi-dimensional data in fitcsvm for SVM training

Hey chaps,
So I have 3-dimensional data at the moment i.e. x=(x_1, x_2, x_3). Each data point vector x=(x_1, etc.) has a label -1 or 1. When I try and include the 1-dimensional data (0nly one x) the training algorithm "fitcsvm" works fine. If I try and use [x_1, x_2, x_3] (3-dimensional), I get the following output:
"Error using classreg.learning.FullClassificationRegressionModel.prepareDataCR (line 137) X and Y do not have the same number of observations."
any ideas guys/gals? thanks

Antworten (0)

Kategorien

Mehr zu Statistics and Machine Learning Toolbox finden Sie in Hilfe-Center und File Exchange

Tags

Gefragt:

am 26 Jun. 2014

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by