# Package weka.classifiers.functions

- Class Summary
  Class | Description
  --- | ---
  GaussianProcesses | * Implements Gaussian processes for regression without hyperparameter-tuning.
  LinearRegression | Class for using linear regression for prediction.
  Logistic | Class for building and using a multinomial logistic regression model with a ridge estimator. There are some modifications, however, compared to the paper of leCessie and van Houwelingen(1992): If there are k classes for n instances with m attributes, the parameter matrix B to be calculated will be an m*(k-1) matrix. The probability for class j with the exception of the last class is Pj(Xi) = exp(XiBj)/((sum[j=1..(k-1)]exp(Xi*Bj))+1) The last class has probability 1-(sum[j=1..(k-1)]Pj(Xi)) = 1/((sum[j=1..(k-1)]exp(Xi*Bj))+1) The (negative) multinomial log-likelihood is thus: L = -sum[i=1..n]{ sum[j=1..(k-1)](Yij * ln(Pj(Xi))) +(1 - (sum[j=1..(k-1)]Yij)) * ln(1 - sum[j=1..(k-1)]Pj(Xi)) } + ridge * (B^2) In order to find the matrix B for which L is minimised, a Quasi-Newton Method is used to search for the optimized values of the m*(k-1) variables.
  MultilayerPerceptron | A classifier that uses backpropagation to learn a multi-layer perceptron to classify instances.
  SGD | Implements stochastic gradient descent for learning various linear models (binary class SVM, binary class logistic regression, squared loss, Huber loss and epsilon-insensitive loss linear regression).
  SGDText | Implements stochastic gradient descent for learning a linear binary class SVM or binary class logistic regression on text data.
  SGDText.Count |
  SimpleLinearRegression | Learns a simple linear regression model.
  SimpleLogistic | Classifier for building linear logistic regression models.
  SMO | Implements John Platt's sequential minimal optimization algorithm for training a support vector classifier. This implementation globally replaces all missing values and transforms nominal attributes into binary ones.
  SMOreg | SMOreg implements the support vector machine for regression.
  VotedPerceptron | Implementation of the voted perceptron algorithm by Freund and Schapire.