How to set class_weight parameter for cost sensitive learning?
\begin{array} {|r|r|}
\hline
- &amp;(1) &amp;(0) \\
\hline
(1) &amp;- &amp;FP\\
\hline
(0) &amp;FN &amp;-\\
\hline
\end{array}
Rows elements are Y_true and column is Y_pred.
FP means, we predicted Positive and it came out False i.e. Class was Negative(0 here).
It means we don't want the Model to mis-classify the Negative class.
So, it implies, we will put a bigger penalty for the Negative class. Hence,
class_weight = {0:3.0.0,1:1.0}