Can you use following code and try;
List<LabeledPoint> points = labeledPoints.collect();
for(int i=0;i<points.size();i++){
System.out.print(points.get(i).label() + "\t");
}
On Tue, Aug 11, 2015 at 2:30 PM, Thushan Ganegedara <thu...@gmail.com>
wrote:
> 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
>
--
Thanks & regards,
Nirmal
Team Lead - WSO2 Machine Learner
Associate Technical Lead - Data Technologies Team, WSO2 Inc.
Mobile: +94715779733
Blog: http://nirmalfdo.blogspot.com/
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