Improving efficiency of SVM using combination of various available kernels


#1

Please leave the following link in the post so we can find the unit module, else replace it with a link to the exact lesson:

Strings and Console Output

Dear friend,
I have shared my folder here: GoogleDrive

I have made 2 codes and 1 PDF and Lower Spine Dataset from machine learning is used from kaggle.

In mittal_20_3.py file i have divided the dataset in train and test and found performance of SVM algorithm.

Now my next task is to improve efficiency of SVM, to do so,

I have two ways,
1) Implementing Kernel Trick that is defining new kernel for SVM.
2) Or making combination of various available kernels and improve efficiency, for that refer attached PDF

In second .py file i tried to manually code for SVM so that kernel can be code uniquely.

I would like to optimize the kernel.

To improve efficiency there are two ways,

  1. Kernel function can be modified, which is nothing but matrix multiplication.
    or
  2. Use various combination of available kernel functions.

Now i m having doubt in coding, how to code for such options in python.

I hope to get some help from fellow members.


#2

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