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Very simple text classification applets: Source files: TextClassifierApplet.java, TextClassifier.java Simple text classification (information).Source files: WekaJ48Applet.java, WekaJ48.java Source files: WekaApplet1.java, Weka1.javaĪpplet using (some of) the options of the J48 algorithm.
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Here you can see some of the algorithms in the works, as well as using different data sets (and providing one of your own in ARFF data format). As Weka (Explorer) is a Java standalone application with a very nice GUI and a lot more to tweak than these applets indicates, you will definitely enjoy Weka more if you use the whole package of your own.
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At the Weka site you can read more about the system as well as downloading it.Īll the MOOC videos are on YouTube. I will not explain everything (in fact, I will not explain very much at all). If using this code, please quote: BMC Bioinformatics, EnzML: multi-label prediction of enzyme classes using InterPro signatures, Luna De Ferrari, Stuart Aitken, Jano van.Here are some small programs purporting to show the versatility of the Weka data mining/machine learning system and what it can do. A Java harness to load data from database, create Weka ARFF and Mulan ARFF+XML files, run machine learning experiments and save the evaluation and predictions to database. This dataset comes with a cost matrix: Good Bad (predicted) Good 0 1 (actual) Bad 5 0 It is worse to class a customer as good when they are bad (5), than it. German Credit data This dataset classifies people described by a set of attributes as good or bad credit risks. 3 3 Click on the token quantity required, this will depend on the type of controller connected to the system.
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