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MATLAB Pattern Recognition Open Free and Easy

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Pattern Recognition in MATLAB

The Pattern Recognition Toolbox for MATLAB® provides an easy to use and robust interface to dozens of pattern classification tools making cross-validation, data exploration, and classifier development rapid and simple. The PRT gives you the power to apply sophisticated data analysis techniques to your problem. If you have data and need to make predictions based on your data, the PRT can help you do more in less time.

Visualize Your Data

The PRT’s prtDataSet objects make using and visualizing your data a breeze. The multiple built in techniques for data visualization will help you interactively understand your data and develop the insights to help you make breakthroughs.

Streamline Your Processing

The PRT provides a wide array of inter-connectable pattern recognition approaches. Every PRT action can be connected to any other PRT actions to enable you to build the powerful processing pipelines to solve the problems you need to solve with a single tool.

Get Answers

Built in cross-validation techniques ensure that your performance estimates are robust, and are indicative of expected operating performance, and built in support for decision making takes the guesswork out of setting optimal thresholds to make binary or M-ary decisions based on your data.




Latest Post


prtDataGenSandP500 and prtDataGenCylinderBellFunnel

Hi everyone, a quick update this time – we added two new prtDataGen* functions to the PRT that people might find useful – prtDataGenSandP500, and prtDataGenCylinderBellFunnel.

Contents

prtDataGenSandP500

prtDataGenSandP500 generates data containing stock-price information from the S&P 500. The information dates back to January 3, 1950, and includes the index’s open, close, volume, and other features.

Check it out:

ds = prtDataGenSandP500;
ds.featureNames
spClose = ds.retainFeatures(5);
plot(spClose.X,'linewidth',2);
title('S&P 500 Closing Value vs. Days since 1/3/1950');
ans = 

    'Date'    'Open'    'High'    'Low'    'Close'    'Volume'    'AdjClose'

If you can do decent prediction on that data… you might be able to make some money :)

Cylinder-Bell-Funnel

prtDataGenCylinderBellFunnel is a tool for generating a synthetic data set which contains a number of time-series, each of which has either a flat plateau (cylinder), a rising (bell) or a falling (funnel) slope.

You can find the specification we used to generate the data here: http://www.cse.unsw.edu.au/~waleed/phd/html/node119.html

And the data was used in an important paper in the data-mining community – Keogh and Lin, Clustering of Time Series Subsequences is Meaningless: Implications for Previous and Future Research. http://www.cs.ucr.edu/~eamonn/meaningless.pdf

ds = prtDataGenCylinderBellFunnel;
imagesc(ds.X);
title(‘Cylinders (1:266), Bells (267:532), and Funnels (533:798)’);

Conclusion

That’s all for now. Hope you enjoy these new data sets, we’re always adding new data to the PRT; let us know what you’d like to see!