Weka - Data mining Tool W eka is a tool for big data and data mining. It is used to various classification, experiments, and analysis over large data sets. Installation Guide -weka You can download Weka from here and follow the normal installation procedure. After completion you will get following window, here you can begin your classification or experiment on different data sets with Weka.
Weka - Data Mining Tool Algorithms: There are a lot of algorithm in weka for various classification and experiments and some the major and widely used are following : Decision tree(J48): NAME: weka.classifiers.trees.J48 SYNOPSIS: Class for generating a pruned or Un pruned C4.5 decision tree. Naïve Bayes: NAME: weka.classifiers.bayes.NaiveBayes SYNOPSIS: Class for a Naive Bayes classifier using estimator classes. Numeric estimator precision values are chosen based on analysis of the training data. For this reason, the classifier is not an UpdateableClassifier (which in typical usage are initialized with zero training instances) KNN(IBK): NAME: weka.classifiers.lazy.IBk SYNOPSIS: K-nearest neighbours classifier. Can select appropriate value of K based on cross-validation. Can also do distance weighting. SVM(LibSVM): NAME: weka.classifiers.functions.LibSVM SYNOPSIS: A wrapper class for the libsvm tools (the libsvm classes,