I am working on how to use KNN to predict a rating for a movie. I use a video and a book to teach myself how to go about it
I tried to run the code I found in the book but it gave me error message. I googled the error message so as to understand it and fix my problem but I don't think I know how to adapt the solutions to my problem. The code is given below:
import numpy as np
import pandas as pd
r_cols = ['user_id', 'movie_id', 'rating']
ratings = pd.read_csv('C:/Users/dell/Downloads/DataScience/DataScience-Python3/ml-100k/u.data', sep='\t', engine='python', names=r_cols, usecols=range(3)) # please enter your file path here. The file is u.data
print(ratings.head())
movieProperties = ratings.groupby('movie_id').agg({'rating': [np.size, np.mean]})
print(movieProperties.head())
movieNumRatings = pd.DataFrame(movieProperties['rating']['size'])
movieNormalizedNumRatings = movieNumRatings.apply(lambda x: (x - np.min(x)) / (np.max(x) - np.min(x)))
print(movieNormalizedNumRatings.head())
movieDict = {}
with open('C:/Users/dell/Downloads/DataScience/DataScience-Python3/ml-100k/u.item') as f: # The file is u.item
temp = ''
for line in f:
fields = line.rstrip('\n').split('|')
movieID = int(fields[0])
name = fields[1]
genres = fields[5:25]
genres = map(int, genres)
movieDict[movieID] = (name, genres, movieNormalizedNumRatings.loc[movieID].get('size'), movieProperties.loc[movieID].rating.get('mean'))
print(movieDict[1])
from scipy import spatial
def ComputeDistance(a, b):
genresA = np.array(list(a[1]))
genresB = np.array(list(b[1]))
genreDistance = spatial.distance.cosine(genresA, genresB)
popularityA = np.array(a[2])
popularityB = np.array(b[2])
popularityDistance = abs(popularityA - popularityB)
return genreDistance + popularityDistance
print(ComputeDistance(movieDict[2], movieDict[4]))
import operator
def getNeighbors(movieID, K):
distances = []
for movie in movieDict:
if (movie != movieID):
dist = ComputeDistance(movieDict[movieID], movieDict[movie])
distances.append((movie, dist))
distances.sort(key=operator.itemgetter(1))
neighbors = []
for x in range(K):
neighbors.append(distance[x][0])
return neighbors
K = 10
avgRating = 0
neighbors = getNeighbors(1, K)
I got this error message from PowerShell:
Traceback(most recent call last):
neighbors = getNeighbors(1, K)
dist = ComputeDistance(movieDict[movieID], movieDict[movie])
genreDistance = spatial.distance.cosine(genresA, genresB)
return correlation(u, v, w=w, centered=False)
uv = np.average(u*v, weights=w)
ValueError: operands could not be broadcast together with shape (19,)(0,)
I got this error message when I tried to debug the problem from ipython terminal:
c:\programdata\anaconda3\lib\site-packages\scipy\spatial\distance.py(695)correlation()
693 u = u - umu
694 v = v - vmu
---> 695 uv = np.average(u*v, weights=w)
696 uu = np.average(np.square(u), weights=w)
697 vv = np.average(np.square(v), weights=w)
