Hello;
I am using the ALS recommendation MLLibb. To select the optimal rank, I have
a number of users who used multiple items as my test. I then get the
prediction on these users and compare it to the observed. I use
the RegressionMetrics to estimate the R^2.
I keep getting a negative value.
r2 = -1.18966999676 explained var = -1.18955347415 count = 11620309
Here is my Pyspark code :
train1.cache()
test1.cache()
numIterations =10
for i in range(10) :
rank = int(40+i*10)
als = ALS(rank=rank, maxIter=numIterations,implicitPrefs=False)
model = als.fit(train1)
predobs =
model.transform(test1).select("prediction","rating").map(lambda p :
(p.prediction,p.rating)).filter(lambda p: (math.isnan(p[0]) == False))
metrics = RegressionMetrics(predobs)
mycount = predobs.count()
myr2 = metrics.r2
myvar = metrics.explainedVariance
print "hooo",rank, " r2 = ",myr2, "explained var = ", myvar, "count
= ",mycount
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