MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: http://ocw.mit.edu/6-034F10 Instructor: Patrick Winston In this lecture, we explore su...
In this post, I want to show how I use NLTK for preprocessing and tokenization, but then apply machine learning techniques (e.g. building a linear SVM using stochastic gradient descent) using Scikit-Learn.
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.
T. Evgeniou, and M. Pontil. Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
, page 109--117. (2004)
S. Kiritchenko, X. Zhu, C. Cherry, and S. Mohammad. Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014)
, page 437--442. Dublin, Ireland, Association for Computational Linguistics, (August 2014)