I’m struggling to get the expected test numbers on the Book Recommendation Machine Learning Challenge .
I deleted all ratings from users with less than 200 ratings and all ratings from books with less than 100 ratings. Then I pass the remaining ratings into a csr_matrix where I replace missing values with 0. When I pass this into my NearestNeighbour-fit, I’m getting other results though. It gives me recommendations, but except for 2 books, they are not the expected ones and the distances are off by magnitudes. Could it be that the dataset changed as well?
These are the recommendations and distances I get for the test:
[
"Where the Heart Is (Oprah's Book Club (Paperback))",
[
['The Surgeon', 61.286213],
['Unspeakable', 61.522354],
['The Perks of Being a Wallflower', 61.579216],
['Gap Creek: The Story Of A Marriage', 61.676575],
['The Weight of Water', 61.75759]
]
]
Down below is the link to my google colab, would be thankful for any feedback
[
"Where the Heart Is (Oprah's Book Club (Paperback))",
[
["The Lovely Bones: A Novel", 0.7230184],
["The Pilot's Wife : A Novel", 0.81926787],
["The Joy Luck Club", 0.81986046],
["The Notebook', 0.823043]
]
]
I don’t Know how to build the model from scratch but i made some changes to pass the challenges the changes are metric should be cosine and algorithm is brute and in the def the recommendation function where you get a list of recommended books make it reverse by using recommended_books[1].reverse() this May you get the result.