You suspect the SVM is underfitting your dataset. Which of the following methods should you adopt to ensure better results?

#1

Increasing the value of C

Decreasing the value of C

Keeping the value of C the same but shuffling the data

Re-initialising the initial weights

#2

Hey @debjanihome, this means our model is classifying most of the points wrong, so we should increase value of c so that, model will give penalty to misclassified points and our model will start fitting again.

Hope this resolved your doubt.
Plz mark the doubt as resolved in my doubts section. :blush: