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## Package weka.classifiers.functions

Class Summary
LeastMedSq | Implements a least median sqaured linear regression utilising the existing weka LinearRegression class to form predictions.
LinearRegression | Class for using linear regression for prediction.
Logistic | Second implementation for building and using a multinomial logistic regression model with a ridge estimator.
MultilayerPerceptron | A Classifier that uses backpropagation to classify instances.
PaceRegression | Class for building pace regression linear models and using them for prediction.
RBFNetwork | Class that implements a normalized Gaussian radial basis function network.
SimpleLinearRegression | Class for learning a simple linear regression model.
SimpleLogistic | Class for building a logistic regression model using LogitBoost.
SMO | Implements John C.
SMOreg | Implements Alex J.Smola and Bernhard Scholkopf sequential minimal optimization algorithm for training a support vector regression using polynomial or RBF kernels.
VotedPerceptron | Implements the voted perceptron algorithm by Freund and Schapire.
Winnow | Implements Winnow and Balanced Winnow algorithms by N.

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