## Regression, Logistic Regression and Maximum Entropy part 2 (code + examples)

Posted on 8 CommentsPosted in Classification, Sentiment Analytics

update: The Python code for Logistic Regression can be forked/cloned from my Git repository. It is also available on PyPi. The relevant information in the blog-posts about Linear and Logistic Regression are also available as a Jupyter Notebook on my Git repository.   Introduction In the previous blog we have seen the theory and mathematics behind the […]

## Regression, Logistic Regression and Maximum Entropy

update: The Python code for Logistic Regression can be forked/cloned from my Git repository. It is also available on PyPi. The relevant information in the blog-posts about Linear and Logistic Regression are also available as a Jupyter Notebook on my Git repository. 1. Introduction One of the most important tasks in Machine Learning are the Classification tasks […]

## Sentiment Analysis with the Naive Bayes Classifier

Posted on 12 CommentsPosted in Machine Learning, Sentiment Analytics

From the introductionary blog we know that the Naive Bayes Classifier is based on the bag-of-words model. With the bag-of-words model we check which word of the text-document appears in a positive-words-list or a negative-words-list. If the word appears in a positive-words-list the total score of the text is updated with +1 and vice versa. […]

## Sentiment Analysis with bag-of-words (part 2)

Posted on 7 CommentsPosted in Machine Learning, Sentiment Analytics

In the previous post we have learned how to do basic Sentiment Analysis with the bag-of-words technique. Here is a short summary: To keep track of the number of occurences of each word, we tokenize the text and add each word to a single list. Then by using a Counter element we can keep track […]

## Sentiment Analysis with bag-of-words

Posted on 7 CommentsPosted in Machine Learning, Sentiment Analytics

update: the dataset containing the book-reviews of Amazon.com has been added to the UCI Machine Learning repository. Introduction: In my previous post I have explained the Theory behind three of the most popular Text Classification methods (Naive Bayes, Maximum Entropy and Support Vector Machines) and told you that I will use these Classifiers for the automatic […]