I see. That's good. Thanks.
Justin
On Sun, Jun 22, 2014 at 4:59 PM, Evan Sparks wrote:
> Oh, and the movie lens one is userid::movieid::rating
>
> - Evan
>
> On Jun 22, 2014, at 3:35 PM, Justin Yip wrote:
>
> Hello,
>
> I am looking into a couple of MLLib data files in
> https://github.com/ap
Oh, and the movie lens one is userid::movieid::rating
- Evan
> On Jun 22, 2014, at 3:35 PM, Justin Yip wrote:
>
> Hello,
>
> I am looking into a couple of MLLib data files in
> https://github.com/apache/spark/tree/master/data/mllib. But I cannot find any
> explanation for these files? Does a
These files follow the libsvm format where each line is a record, the first
column is a label, and then after that the fields are offset:value where offset
is the offset into the feature vector, and value is the value of the input
feature.
This is a fairly efficient representation for sparse b
Hi Shuo,
Yes. I was reading the guide as well as the sample code.
For example, in
http://spark.apache.org/docs/latest/mllib-linear-methods.html#linear-support-vector-machine-svm,
now where in the github repository I can find the file: sc.textFile(
"mllib/data/ridge-data/lpsa.data").
Thanks.
Jus
Hi Shuo,
Yes. I was reading the guide as well as the sample code.
For example, in
http://spark.apache.org/docs/latest/mllib-linear-methods.html#linear-support-vector-machine-svm,
nowhere in the github repository I can find the file: sc.textFile(
"mllib/data/ridge-data/lpsa.data").
Thanks.
Justi
Hi, you might find http://spark.apache.org/docs/latest/mllib-guide.html
helpful.
On Sun, Jun 22, 2014 at 2:35 PM, Justin Yip wrote:
> Hello,
>
> I am looking into a couple of MLLib data files in
> https://github.com/apache/spark/tree/master/data/mllib. But I cannot find
> any explanation for th
