He replied to me. Forwarding to the mailing list.

---------- Forwarded message ----------
From: Aditya Vyas <adityavya...@gmail.com>
Date: Tue, Oct 25, 2016 at 8:16 PM
Subject: Re: Need help with SVM
To: Aseem Bansal <asmbans...@gmail.com>


Hello,
Here is the public gist:https://gist.github.com/a
ditya1702/760cd5c95a6adf2447347e0b087bc318

Do tell if you need more information

Regards,
Aditya

On Tue, Oct 25, 2016 at 8:11 PM, Aseem Bansal <asmbans...@gmail.com> wrote:

> Is there any labeled point with label 0 in your dataset?
>
> On Tue, Oct 25, 2016 at 2:13 AM, aditya1702 <adityavya...@gmail.com>
> wrote:
>
>> Hello,
>> I am using linear SVM to train my model and generate a line through my
>> data.
>> However my model always predicts 1 for all the feature examples. Here is
>> my
>> code:
>>
>> print data_rdd.take(5)
>> [LabeledPoint(1.0, [1.9643,4.5957]), LabeledPoint(1.0, [2.2753,3.8589]),
>> LabeledPoint(1.0, [2.9781,4.5651]), LabeledPoint(1.0, [2.932,3.5519]),
>> LabeledPoint(1.0, [3.5772,2.856])]
>>
>> ------------------------------------------------------------
>> ----------------------------
>> from pyspark.mllib.classification import SVMWithSGD
>> from pyspark.mllib.linalg import Vectors
>> from sklearn.svm import SVC
>> data_rdd=x_df.map(lambda x:LabeledPoint(x[1],x[0]))
>>
>> model = SVMWithSGD.train(data_rdd, iterations=1000,regParam=1)
>>
>> X=x_df.map(lambda x:x[0]).collect()
>> Y=x_df.map(lambda x:x[1]).collect()
>>
>> ------------------------------------------------------------
>> ----------------------------
>> pred=[]
>> for i in X:
>>   pred.append(model.predict(i))
>> print pred
>>
>> [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
>> 1,
>> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
>> 1]
>>
>>
>> My dataset is as follows:
>> <http://apache-spark-user-list.1001560.n3.nabble.com/file/n2
>> 7955/Screen_Shot_2016-10-25_at_2.png>
>>
>>
>> Can someone please help?
>>
>>
>>
>> --
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>>
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>

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