Open sbhakat opened 5 years ago
Simple question: How do I get the exact value of SVM coefficient for each tICs. It is a bit hard to see from the plot. Any script?
I am confused here. Have you tried printing out the coefficients instead of plotting them?
What is the meaning of this line train_X.sum(axis=1)[300:].std() and the output 2.2081068901447987
I was calculating the standard deviation of each feature after summing them together. I am not sure I remember why exactly tbh.
I generated 4 tICs from the 4 dihedral features presented in the attached notebook. Now I want to train the tICs to see which tIC is more dominant over the other. And in this regard I want to generate a plot similar like SVM co-efficients vs Feature index mentioned in this notebook https://github.com/msultan/SML_CV/blob/master/alanine_example/01-svm_example.ipynb .
First question:
I tried something like that just substituting the original script a bit to train the tICA features
train_X.sum(axis=1)[300:].std()
What is the meaning of this line
train_X.sum(axis=1)[300:].std()
and the output2.2081068901447987
The I plotted the tIC0 vs SVM co-efficient using the following script and got an output like following
Simple question: How do I get the exact value of SVM coefficient for each tICs. It is a bit hard to see from the plot. Any script?