Ah, that makes perfect sense. Thanks for the concise explanation!
On Thu, Aug 7, 2014 at 9:14 PM, Xiangrui Meng wrote:
> ratings.map{ case Rating(u,m,r) => {
> val pred = model.predict(u, m)
> (r - pred)*(r - pred)
> }
> }.mean()
>
> The code doesn't work because the userFeatures and
ratings.map{ case Rating(u,m,r) => {
val pred = model.predict(u, m)
(r - pred)*(r - pred)
}
}.mean()
The code doesn't work because the userFeatures and productFeatures
stored in the model are RDDs. You tried to serialize them into the
task closure, and execute `model.predict` on an execu
Hi Jay,
I've had the same problem you've been having in Question 1 with a synthetic
dataset. I thought I wasn't producing the dataset well enough. This seems to
be a bug. I will open a JIRA for it.
Instead of using:
ratings.map{ case Rating(u,m,r) => {
val pred = model.predict(u, m)
(r
On Thu, Aug 7, 2014 at 9:06 PM, Jay Hutfles wrote:
> 0,0,5
> 0,1,5
> 0,2,0
> 0,3,0
> 1,0,5
> 1,3,0
> 2,1,4
> 2,2,0
> 3,0,0
> 3,1,0
> 3,2,5
> 3,3,4
> 4,0,0
> 4,1,0
> 4,2,5
> val rank = 10
This is likely the problem? your rank is actually larger than the
number of users or items. The error could p
