I am new to python and couldn't find the answer to this. Referring to the code at the end of the message, can I know what does the part "for item, total in totals.items()" in the line below mean?
rankings = [(total/simSums[item], item) for item, total in totals.items()]
Also, the code failed and said
AttributeError: 'dict' object has no attribute 'predictors'
when I changed all instances of "item(s)" in the code to "predictor(s)". Why is that so?
# Return the Pearson correlation coefficient for p1 and p2
def sim_person(prefs, p1, p2):
# Get the list of shared_items
si={}
for item in prefs[p1]:
if item in prefs[p2]:si[item]=1
# Find the number of elements
n=len(si)
# if they have no ratings in common, return 0
if n==0: return 0
# Add up all the preferences
sum1 = sum([prefs[p1][it] for it in si])
sum2 = sum([prefs[p2][it] for it in si])
# Sum up the squares
sum1Sq = sum([pow(prefs[p1][it],2) for it in si])
sum2Sq = sum([pow(prefs[p2][it],2) for it in si])
# Sum up the products
pSum = sum([prefs[p1][it]*prefs[p2][it] for it in si])
# Calculate Person score
num = pSum - (sum1*sum2/n)
den = sqrt((sum1Sq - pow(sum1,2)/n)*(sum2Sq - pow(sum2,2)/n))
if den == 0: return 0
r = num/den
return r
# Returns the best matches for person from the prefs dictionary.
# Number of results and similarity function are optional params.
def topMatch(prefs, person, n=5, similarity=sim_person):
scores = [(similarity(prefs, person, other), other)
for other in prefs if other!=person]
# Sort the list so the highest scores appear at the top
scores.sort()
scores.reverse()
return scores[0:n]
# Gets recommendations for a person by using a weighted average
# of every other user's rankings
def getRecommendations(prefs, person, similarity=sim_person):
totals = {}
simSums = {}
for other in prefs:
# don't compare me to myself
if other == person: continue
sim = similarity(prefs, person, other)
# ignore scores of zero of lower
if sim<=0: continue
for item in prefs[other]:
# only score movies I haven't seen yet
if item not in prefs[person] or prefs[person][item]==0:
# Similarity * Score
totals.setdefault(item, 0)
totals[item]+=prefs[other][item]*sim
# Sum of similarities
simSums.setdefault(item, 0)
simSums[item]+=sim
# Create the normalized list
rankings = [(total/simSums[item], item) for item, total in totals.items()]
# Return the sorted list
rankings.sort()
rankings.reverse()
return rankings
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python
The dict.items iterates over the key-value pairs of a dictionary. Therefore for key, value in dictionary.items() will loop over each pair. This is documented information and you can check it out in the official web page, or even easier, open a python console and type help(dict.items). And now, just as an example:
>>> d = {'hello': 34, 'world': 2999}
>>> for key, value in d.items():
... print key, value
...
world 2999
hello 34
The AttributeError is an exception thrown when an object does not have the attribute you tried to access. The class dict does not have any predictors attribute (now you know where to check it :) ), and therefore it complains when you try to access it. As easy as that.
#Try without dot notation
sample_dict = {'name': 'John', 'age': 29}
print(sample_dict['name']) # John
print(sample_dict['age']) # 29
Source: Stackoverflow.com