In this post you will see 5 recipes of supervised classification algorithms applied to small standard datasets that are provided with the scikit-learn library.
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.
A. Dargahi Nobari, N. Reshadatmand, and M. Neshati. Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, page 2035–2038. New York, NY, USA, Association for Computing Machinery, (2017)
R. Girju, P. Nakov, V. Nastase, S. Szpakowicz, P. Turney, and D. Yuret. Proceedings of the 4th International Workshop on Semantic Evaluations, page 13--18. Stroudsburg, PA, USA, Association for Computational Linguistics, (2007)
L. Hettinger, A. Zehe, A. Dallmann, and A. Hotho. INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft, page 191-204. Bonn, Gesellschaft für Informatik e.V., (2019)