Number of users is 1055 Number of items is 4 Ratings values are either 120, 20, 0
From: Nick Pentreath <nick.pentre...@gmail.com> Sent: Wednesday, June 26, 2019 6:03 AM To: user@spark.apache.org Subject: [EXTERNAL] - Re: Problem with the ML ALS algorithm This means that the matrix that ALS is trying to factor is not positive definite. Try increasing regParam (try 0.1, 1.0 for example). What does the data look like? e.g. number of users, number of items, number of ratings, etc? On Wed, Jun 26, 2019 at 12:06 AM Steve Pruitt <bpru...@opentext.com<mailto:bpru...@opentext.com>> wrote: I get an inexplicable exception when trying to build an ALSModel with the implicit set to true. I can’t find any help online. Thanks in advance. My code is: ALS als = new ALS() .setMaxIter(5) .setRegParam(0.01) .setUserCol("customer") .setItemCol("item") .setImplicitPrefs(true) .setRatingCol("rating"); ALSModel model = als.fit(training); The exception is: org.apache.spark.ml.optim.SingularMatrixException: LAPACK.dppsv returned 6 because A is not positive definite. Is A derived from a singular matrix (e.g. collinear column values)? at org.apache.spark.mllib.linalg.CholeskyDecomposition$.checkReturnValue(CholeskyDecomposition.scala:65) ~[spark-mllib_2.11-2.3.1.jar:2.3.1] at org.apache.spark.mllib.linalg.CholeskyDecomposition$.solve(CholeskyDecomposition.scala:41) ~[spark-mllib_2.11-2.3.1.jar:2.3.1] at org.apache.spark.ml.recommendation.ALS$CholeskySolver.solve(ALS.scala:747) ~[spark-mllib_2.11-2.3.1.jar:2.3.1]
