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It contains a serious bug. #99

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rabintang opened this issue Jun 30, 2014 · 1 comment

rabintang commented Jun 30, 2014

In knn/classes.py UserBasedRecommender.estimate_preference, the following codes

prefs = prefs[~np.isnan(prefs)] # prefs = [1, 2, 4]
similarities = similarities[~np.isnan(prefs)] # similarities = [0.1, 0.2, 0.3], but actually it show be [0.1, 0.2, 0.4]
prefs_sim = np.sum(prefs[~np.isnan(similarities)] * similarities[~np.isnan(similarities)])
have a serious bug, assuming that initial prefs = [1, 2, non, 4], similarities = [0.1, 0.2, 0.3, 0.4].

tyutjxs commented Apr 27, 2018

do you have resolved it?

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