{"action":"created","issue":{"url":"https://api.github.com/repos/NicolasHug/Surprise/issues/218","repository_url":"https://api.github.com/repos/NicolasHug/Surprise","labels_url":"https://api.github.com/repos/NicolasHug/Surprise/issues/218/labels{/name}","comments_url":"https://api.github.com/repos/NicolasHug/Surprise/issues/218/comments","events_url":"https://api.github.com/repos/NicolasHug/Surprise/issues/218/events","html_url":"https://github.com/NicolasHug/Surprise/issues/218","id":371840417,"node_id":"MDU6SXNzdWUzNzE4NDA0MTc=","number":218,"title":"Own Prediction Alogrithm: Adjusted KNN With Means","user":{"login":"TamTSE2301","id":40611425,"node_id":"MDQ6VXNlcjQwNjExNDI1","avatar_url":"https://avatars1.githubusercontent.com/u/40611425?v=4","gravatar_id":"","url":"https://api.github.com/users/TamTSE2301","html_url":"https://github.com/TamTSE2301","followers_url":"https://api.github.com/users/TamTSE2301/followers","following_url":"https://api.github.com/users/TamTSE2301/following{/other_user}","gists_url":"https://api.github.com/users/TamTSE2301/gists{/gist_id}","starred_url":"https://api.github.com/users/TamTSE2301/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/TamTSE2301/subscriptions","organizations_url":"https://api.github.com/users/TamTSE2301/orgs","repos_url":"https://api.github.com/users/TamTSE2301/repos","events_url":"https://api.github.com/users/TamTSE2301/events{/privacy}","received_events_url":"https://api.github.com/users/TamTSE2301/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":11,"created_at":"2018-10-19T07:38:05Z","updated_at":"2018-10-22T21:11:37Z","closed_at":null,"author_association":"NONE","body":"Hi,\r\n\r\nI want to adjust the KNN alogrithm a little bit. My idea is that before you specify k_neighbours by heapq.nlargest, I want to ignore the similarities results that are smaller than a threshold (min_s). Specifically:\r\n```\r\n        for (n,sim,r) in neighbors:\r\n            if sim < min_s:\r\n                sim = 0\r\n```\r\n\r\nOf course, I am trying to check the accuracy for this adjustment. However when I built my own alogrithm like your guidlines, i receive the following errors:\r\n\r\n> TypeError: compute_similarities() got an unexpected keyword argument 'verbose'\r\n\r\nThese are the libs I have imported. The code Class Adjusted_KNNWithMeans is the same as your KNNWithMeans; except the change I mentioned above.\r\n\r\n```\r\nfrom surprise import Reader, Dataset, trainset\r\nfrom surprise import SVD, evaluate, SVDpp\r\nfrom surprise.model_selection import cross_validate, train_test_split\r\nfrom surprise.model_selection import train_test_split\r\nfrom surprise import accuracy\r\nfrom surprise import PredictionImpossible\r\nfrom surprise import AlgoBase\r\nfrom surprise.prediction_algorithms.knns import SymmetricAlgo\r\nfrom __future__ import (absolute_import, division, print_function,\r\n                        unicode_literals)\r\nimport numpy as np\r\nfrom six import iteritems\r\nimport heapq\r\n```\r\nThank you very much.\r\n"},"comment":{"url":"https://api.github.com/repos/NicolasHug/Surprise/issues/comments/431988304","html_url":"https://github.com/NicolasHug/Surprise/issues/218#issuecomment-431988304","issue_url":"https://api.github.com/repos/NicolasHug/Surprise/issues/218","id":431988304,"node_id":"MDEyOklzc3VlQ29tbWVudDQzMTk4ODMwNA==","user":{"login":"TamTSE2301","id":40611425,"node_id":"MDQ6VXNlcjQwNjExNDI1","avatar_url":"https://avatars1.githubusercontent.com/u/40611425?v=4","gravatar_id":"","url":"https://api.github.com/users/TamTSE2301","html_url":"https://github.com/TamTSE2301","followers_url":"https://api.github.com/users/TamTSE2301/followers","following_url":"https://api.github.com/users/TamTSE2301/following{/other_user}","gists_url":"https://api.github.com/users/TamTSE2301/gists{/gist_id}","starred_url":"https://api.github.com/users/TamTSE2301/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/TamTSE2301/subscriptions","organizations_url":"https://api.github.com/users/TamTSE2301/orgs","repos_url":"https://api.github.com/users/TamTSE2301/repos","events_url":"https://api.github.com/users/TamTSE2301/events{/privacy}","received_events_url":"https://api.github.com/users/TamTSE2301/received_events","type":"User","site_admin":false},"created_at":"2018-10-22T21:11:37Z","updated_at":"2018-10-22T21:11:37Z","author_association":"NONE","body":"Again. If I still let the verbose argument in **compute_similarities**(), I still get the error."}}
{"actor":{"display_login":"TamTSE2301"}}