I am trying to find the most valuable features by applying feature selection methods to my dataset. Im using the SelectKBest function for now. I can generate the score values and sort them as I want, but I don’t understand exactly how this score value is calculated. I know that theoretically high score is more valuable, but I need a
Tag: feature-selection
Interpreting logistic regression feature coefficient values in sklearn
I have fit a logistic regression model to my data. Imagine, I have four features: 1) which condition the participant received, 2) whether the participant had any prior knowledge/background about the phenomenon tested (binary response in post-experimental questionnaire), 3) time spent on the experimental task, and 4) participant age. I am trying to predict whether participants ultimately chose option A
Top 10 features SVC with rbf kernel
I’m trying to get the top 10 most informative (best) features for a SVM classifier with RBF kernel. As I’m a beginner in programming, I tried some codes that I found online. Unfortunately, none work. I always get the error: ValueError: coef_ is only available when using a linear kernel. This is the last code I tested: Does someone no