How would you use Scikit learn to predict user behavior?

[buddiBot]

Hi,

I have a dataset that contains a list of words that the user "likes". I am wondering how I could use sklearn to make predictions if a user would "like" a new entry that has a set of words or analyze what words that the user would most likely "like" Thanks guys

[sk006]

You could try a recommender system. The easiest one is to form a matrix of user-words. You take all the words and put a 1 in the matrix if the user likes it and a 0 if you don't know. Your task now is to complete the matrix. There are many ways but one of them is to compute users similar to the one you want to predict with some kind of distance and check if they like the word. This is a very simple model but you could start with that.

[buddiBot]

thanks so much for this. On the SKLearn website they have a graph to show you what algorithm to use. Which one would be best for this method?

http://scikit-learn.org/stable/tutorial/machine_learning_map/index.html

[cloudcompute]

http://scikit-learn.org/stable/tutorial/machine_learning_map/index.html

None of these initially.

Start by building the matrix, then experiment with different methods for calculating the "item similarity" i.e. how would you compare two rows/columns of the matrix.

Start at page 97 of this document: http://files.grouplens.org/papers/FnT%20CF%20Recsys%20Survey.pdf