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need to find the k for train test of svm. The work is 95% done.

Most of the code is built. Only thing you have to do is to compute EER for every k rows where k is from 1 to 10. This is how you can see whether your svm is performing better towards larger k. Larger k means the svm has learned more data rows.

So, instead of getting 1 eer for the whole data you should get 10 eer.

So, right now as per your email your svm I assume is giving 1% error at k=1, since you have whole data.

Currently i have EER 0.1. I need to get it close to 0 to 0.04 as i increase the k. This is the paper i'm emulating the code for [login to view URL]

Author claims that in all scenario his error rate is 0 to 0.04%. I want to do the same.

1. [login to view URL] is the dataset

2. Touchalytics_colab is the code.

3. Image to get an idea how to do it.

The main task is to create k fold so as i increase my fold my error rate should go down from 0.1 to almost 0.

Taidot: Machine Learning (ML), Tensorflow, Python, Scikit Learn

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( 4 arvostelua ) Potsdam, United States

Projektin tunnus: #22174023

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segredominic

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wwwTom

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topman068001

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Intel1994

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