Hello;
I am trying to get the optimal number of factors in ALS. To that end, i am
scanning various values and evaluating the RSE. DO i need to un-perisist the
RDD between loops or will the resources (memory) get automatically deleted
and re-assigned between iterations.
for i in range(5):
rank = 5 +int(i )
#imodel = ALS.trainImplicit(smallratings, rank, numIterations)
imodel = ALS.train(smallratings, rank, numIterations)
predictions = imodel.predictAll(testdata).map(lambda r: ((r[0], r[1]),
r[2]))
ratesAndPreds = smallratings.map(lambda r: ((r[0], r[1]),
r[2])).join(predictions)
MSE = ratesAndPreds.map(lambda r: (r[1][0] - r[1][1])**2).reduce(lambda
x, y: x + y) / ratesAndPreds.count()
print "ho ho ", rank, " ", MSE
predictions.unpersist()
ratesAndPreds.unpersist()
--
View this message in context:
http://apache-spark-user-list.1001560.n3.nabble.com/Un-persist-RDD-in-a-loop-tp23414.html
Sent from the Apache Spark User List mailing list archive at Nabble.com.
---------------------------------------------------------------------
To unsubscribe, e-mail: user-unsubscr...@spark.apache.org
For additional commands, e-mail: user-h...@spark.apache.org
