Code covered by the BSD License  

Highlights from
Machine Learning with MATLAB

4.6

4.6 | 5 ratings Rate this file 280 Downloads (last 30 days) File Size: 882 KB File ID: #42744
image thumbnail

Machine Learning with MATLAB

by

 

05 Aug 2013 (Updated )

These are the supporting MATLAB files for the MathWorks webinar of the same name.

| Watch this File

File Information
Description

** Update: The webinar recording is available at:
http://www.mathworks.com/videos/machine-learning-with-matlab-81984.html

In this webinar you will learn how to get started using machine learning tools to detect patterns and build predictive models from your datasets. In this session, you will learn about several machine learning techniques available in MATLAB and how to quickly explore your data, evaluate machine learning algorithms, compare the results, and apply the best machine learning for your problem.

Highlights include unsupervised and supervised machine learning techniques including:
• K-means and other clustering tools
• Neural Networks
• Decision trees and ensemble learning
• Naïve Bayes Classification
• Linear, logistic and nonlinear regression

Acknowledgements

Rotate X Labels( Ax, Angle, Varargin ) and Plot Groups Of Stacked Bars inspired this file.

Required Products Fuzzy Logic Toolbox
Neural Network Toolbox
Parallel Computing Toolbox
Statistics Toolbox
MATLAB
MATLAB release MATLAB 8.1 (R2013a)
Tags for This File   Please login to tag files.
Please login to add a comment or rating.
Comments and Ratings (7)
25 Nov 2014 Azadeh

I run MachineLearning.m on sample dataset bank-full.csv and got this error:

Default value is not a member of type "nntype.performance_fcn".
Error using nnetParamInfo (line 28)
Too many input arguments.

Error in patternnet>get_info (line 85)
info = nnfcnNetwork(mfilename,'Pattern Recognition Neural Network',fcnversion, ...

Error in patternnet (line 41)
if isempty(INFO), INFO = get_info; end

Error in NNfun (line 18)
net = patternnet(hiddenLayerSize);

Error in MachineLearning (line 191)
[~, net] = NNfun(XtrainNN,YtrainNN);

14 Aug 2014 Mehmet  
24 Apr 2014 Abhishek Gupta

Hi Remi,

The data for the classification example is available here:
http://archive.ics.uci.edu/ml/datasets/Bank+Marketing

I believe that I have mentioned this in the readme.

21 Apr 2014 Rémi Larouche

The CSV file is missing ('bank-full.csv').

28 Dec 2013 Wenwu

Thanks, nice webinar and supplementary files.

16 Dec 2013 PRIYA  
08 Dec 2013 Sergey  
Updates
05 Aug 2013

Added webinar link

30 Jul 2014

Updated webinar link

Contact us