Feature Selection Techniques

Question

I am completely new to statistical modelling.I wanted to know what are the feature selection techniques.

Say I have 10 variables but I need to what are actual important one's among them.

I have read about feature selection on internet and came to know few of the techniques:

1. Correlation
2. Forward Selection
3. Backward Elimination

But I am not getting how can I use them. How can a correlation be used in feature selection. How to perform a Forward Selection/Backward Elimination etc.

What models I can use for feature selection. I just want a high level overview of it. When to use what

Some one help me to get started

Answer 1

Correlation - In this approach we see how the target variable is correlated with the predictors and choose the ones which are highly correlated and ignore the others.

Forward Selection - In this we start with 0 predictors and check the model performance. And then at every stage we add one of the predictor which gives the best model performance.

Backward Selection - In this we start with all the predictors. And then at every stage we remove one of the predictors which gives the better model performance.