improving the recommendation results as an exercisei want to challenge you to go and make those recommendations even better solet' talk about some ideas haveand maybe you'll have some of your own too that you can actually try out and experiment withget your hands dirtyand try to make better movie recommendations okaythere' lot of room for improvement still on these recommendation results there' lot of decisions we made about how to weigh different recommendation results based on your rating of that item that it came fromor what threshold you want to pick for the minimum number of people that rated two given movies sothere' lot of things you can tweaka lot of different algorithms you can tryand you can have lot of fun with trying to make better movie recommendations out of the system soif you're feeling up to iti' challenging you to go and do just thathere are some ideas on how you might actually try to improve upon the results in this firstyou can just go ahead and play with the *ufncbtfe$'jqzoc file and tinker with it sofor examplewe saw that the correlation method actually had some parameters for the correlation computationwe used pearson in our examplebut there are other ones you can look up and try outsee what it does to your results we used minimum period value of maybe that' too highmaybe it' too lowwe just kind of picked it arbitrarily what happens if you play with that valueif you were to lower that for examplei would expect you to see some new movies maybe you've never heard ofbut might still be good recommendation for that person orif you were to raise it higheryou would seeyou know nothing but blockbusters sometimes you have to think about what the result is that you want out of recommender system is there good balance to be had between showing people movies that they've heard of and movies that they haven' heard ofhow important is discovery of new movies to these people versus having confidence in the recommender system by seeing lot of movies that they have heard ofso againthere' sort of an art to that we can also improve upon the fact that we saw lot of movies in the results that were similar to gone with the windeven though didn' like gone with the wind you know we weighted those results lower than similarities to movies that enjoyedbut maybe those movies should actually be penalized if hated gone with the wind that muchmaybe similarities to gone with the windlike the wizard of ozshould actually be penalized andyou know lowered in their score instead of raised at all