MACHINE LEARNING: Neural Networks, Decision Trees and Support Vector Machine with IBM SPSS Modeler

Machine Learning techniques are intended to extract the knowledge contained in the data through models and other appropriate techniques. Within Machine Learning techniques there are two fundamental types: supervised learning techniques and unsupervised learning techniques. Supervised learning techniques include all those that use a model in which there are dependent variables and independent variables. The purpose of these techniques is usually prediction or classification of both at the same time. Neural networks, decision trees, and SVM models are supervised learning machine learning techniques for prediction and classification. It is precisely these techniques that are developed in this book using IBM SPSS Modeler software.