I need a suggestion on how to do analyze this type of data. I want to perform a sentiment analysis or linear regression on it as a machine learning tool. The predictor is score.
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 a LinearRegression classifier in WEKA which yields:
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 app. Is there another way to process this data and yield a linear regression equation not using WEKA. Any other suggestions on how to analyze it other than linear regression? I've already implemented a decision tree.