Mood Analysis / Linear Regression (Django)

Question

I need a suggestion on how to parse this data type. I want to perform a mood analysis or linear regression on it as a machine learning tool. The predictor is an estimate.

color type make new score red truck ford y 2 black sedan chevy n 4 silver sedan nissan y 5 silver truck nissan n 2 black coupe toyota y 1 blue van honda y 1 red truck toyota n 4 red coupe ford n 2 black sedan ford y 1 blue truck toyota y 4 white coupe chevy y 3 white van toyota n 5 red van ford y 2 silver truck nissan n 3 black sedan honda n 1 silver truck chevy y 4 red truck chevy y 5 white coupe honda n 5 blue sedan chevy n 2 blue van nissan y 3 

I can run the LinearRegression classifier in WEKA, which gives:

 score = 1.6 ( color=red,silver,white) + 1.8 (make=honda,nissan,toyota,chevy) + 0.55 

However, I would like to implement this in Django for a web application. Is there any other way to process this data and get a linear regression equation that does not use WEKA. Any other suggestions on how to analyze it other than linear regression? I have already implemented a decision tree.

Answer 1

You can use scikit-learn as your computer learning library, and especially its linear regression . This example may also be useful.

In addition, you can always bind the Weka API to your application or, alternatively, implement linear regression yourself, this is a fairly simple algorithm for implementing this library of matrix algebra.