The experiment was conducted under R. The source code accompanies this document. My idea, besides the theme of the linear classifiers that concerns us, is also to describe the different stages of the elaboration of an experiment for the comparison of learning techniques. In addition, we show also the results provided by the linear approaches implemented in various tools such as Tanagra, Knime, Orange, Weka and RapidMiner.

**Keywords**: linear classifier, naive bayes, linear discriminant analysis, logistic regression, perceptron, neural network, linear svm, support vector machine, decision tree, rpart, random forest, k-nn, nearest neighbors, e1071 package, nnet package, rf package, class package

**Components**: NAIVE BAYES CONTINUOUS, LINEAR DISCRIMINANT ANALYSIS, BINARY LOGISTIC REGRESSION, MULTILAYER PERCEPTRON, SVM

**Tutorial**: en_Tanagra_Linear_Classifier.pdf

**Programs and dataset**: linear_classifier.zip

**References**:

Wikipedia, "Linear Classifier".