A collection of command-line tools for researchers in machine learning, data mining, and related fields. All of the functionality is also provided in a clean C++ class library
In the previous post on Support Vector Machines (SVM), we looked at the mathematical details of the algorithm. In this post, I will be discussing the practical implementations of SVM for classification as well as regression. I will be using the iris dataset as an example for the classification problem, and a randomly generated data as an example for the regression problem.
This is a repository of databases, domain theories and data generators that are used by the machine learning community for the empirical analysis of machine learning algorithms.
Platform for sharing and evaluation of intelligent algorithms. Data mining data, experiments, datasets, performance analysis, data repository, challenges. Research and applications, prediction. Data mining and machine learning
J. Rennie, и A. McCallum. Proceedings of the Sixteenth International Conference on Machine Learning, стр. 335--343. San Francisco, CA, USA, Morgan Kaufmann Publishers Inc., (1999)