Data Envelopment Analysis, also known as DEA, is a non-parametric method for performing frontier analysis. It uses linear programming to estimate the efficiency of multiple decision-making units and it is commonly used in production, management and economics. The technique was first proposed by Charnes, Cooper and Rhodes in 1978 and since then it became a […]
In this article we will discuss how you can build easily a simple Facebook Sentiment Analysis tool capable of classifying public posts (both from users and from pages) as positive, negative and neutral. We are going to use Facebook’s Graph API Search and the Datumbox API 1.0v. Similar to the Twitter Sentiment Analysis tool that […]
In previous articles we have discussed the theoretical background of Naive Bayes Text Classifier and the importance of using Feature Selection techniques in Text Classification. In this article, we are going to put everything together and build a simple implementation of the Naive Bayes text classification algorithm in JAVA. The code of the classifier is […]
Recently, I have been refreshing my knowledge of Machine Learning by taking Andrew Ng’s excellent Stanford Machine Learning course online. The lecture module on Neural Networks ends with an intriging motivating video of the ALVINN autonomous car driving itself along normal roads at CMU in the mid 90s.
<p><em>This is an archive of Dan Weinreb's comments on Symbolics and Lisp machines.</em></p> <h3 id="rebuttal-to-stallman-s-story-about-the-formation-of-symbolics-and-lmi">Rebuttal to Stallman’s Story About The Formation of Symbolics and LMI</h3> <p>Richard Stallman has been telling a story about the origins of the Lisp machine companies, and the effects on the M.I.T. Artificial Intelligence Lab, for many years. He has published it in a book, and in a widely-referenced paper, which you can find
