I used the following snippet

for(int i=0;i<labeledPoints.collect().size();i++){
            System.out.print(labeledPoints.collect().get(i).label() + "\t");
            }

in the public MLModel build() throws MLModelBuilderException in
DeeplearningModelBuilder.java


On Tue, Aug 11, 2015 at 6:17 PM, Nirmal Fernando <nir...@wso2.com> wrote:

> Hi thushan,
>
> We need more info. What did you exactly print and where?
>
> On Tue, Aug 11, 2015 at 12:47 PM, Thushan Ganegedara <thu...@gmail.com>
> wrote:
>
>> Hi,
>>
>> I found the potential cause of the poor accuracy for the leaf dataset. It
>> seems the data read into ML is wrong.
>>
>> I have attached the data file as a CSV (classes are in the last column)
>>
>> However, when I print out the labels of the read data (classes), it looks
>> something like below. Clearly there aren't this many "3.0" classes and
>> there should be classes up to 36.0.
>>
>> Is this caused by a bug?
>>
>> 1.0     1.0     1.0     1.0     1.0     1.0     1.0     1.0     1.0
>> 1.0     1.0     1.0     12.0    12.0    12.0    12.0    12.0    12.0
>> 12.0    12.0    12.0    12.0    13.0    13.0    13.0    13.0    13.0    13.0
>> 13.0    13.0    13.0    13.0    14.0    14.0    14.0    14.0    14.0
>> 14.0    14.0    14.0    15.0    15.0    15.0    15.0    15.0    15.0
>> 15.0    15.0    15.0    15.0    15.0    15.0    16.0    16.0    16.0    16.0
>> 16.0    16.0    16.0    16.0    17.0    17.0    17.0    17.0    17.0
>> 17.0    17.0    17.0    17.0    17.0    18.0    18.0    18.0    18.0
>> 18.0    18.0    18.0    18.0    18.0    18.0    18.0    19.0    19.0    19.0
>> 19.0    19.0    19.0    19.0    19.0    19.0    19.0    19.0    19.0
>> 19.0    19.0    2.0     2.0     2.0     2.0     2.0     2.0     2.0
>> 2.0     2.0     2.0     2.0     2.0     2.0     3.0     3.0     3.0     3.0
>> 3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0
>> 3.0     3.0     3.0     4.0     4.0     4.0     4.0     4.0     4.0
>> 4.0     4.0     4.0     4.0     4.0     4.0     5.0     5.0     5.0     5.0
>> 5.0     5.0     5.0     5.0     5.0     5.0     5.0     5.0     5.0
>> 6.0     6.0     6.0     6.0     6.0     6.0     6.0     6.0     6.0
>> 6.0     6.0     6.0     7.0     7.0     7.0     7.0     7.0     7.0     7.0
>> 7.0     7.0     7.0     3.0     3.0     3.0     3.0     3.0     3.0
>> 3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0
>> 3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0
>> 3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0
>> 3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0
>> 3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0
>> 3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0
>> 3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0
>> 3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0
>> 3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0
>> 3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0
>> 3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0
>> 3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0
>> 3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0
>> 3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0
>> 3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0
>> 3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0
>> 3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0     3.0
>> 3.0     3.0     3.0     3.0
>>
>> --
>> Regards,
>>
>> Thushan Ganegedara
>> School of IT
>> University of Sydney, Australia
>>
>
>
>
> --
>
> Thanks & regards,
> Nirmal
>
> Team Lead - WSO2 Machine Learner
> Associate Technical Lead - Data Technologies Team, WSO2 Inc.
> Mobile: +94715779733
> Blog: http://nirmalfdo.blogspot.com/
>
>
>


-- 
Regards,

Thushan Ganegedara
School of IT
University of Sydney, Australia
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