April 2018
Beginner
552 pages
13h 58m
English
import json import numpy as np from euclidean_score import euclidean_score from pearson_score import pearson_score from search_similar_user import search_similar_user
# Generate recommendations for a given user
def recommendation_generated(dataset, user):
if user not in dataset:
raiseTypeError('User ' + user + ' not present in the dataset')
sumofall_scores= {} identical_sums= {} for u in [x for x in dataset if x != user]: identical_score= pearson_score(dataset, user, u) if identical_score<= ...