Write a Python code to select features using any wrapper method $($such as Recursive Feature Elimination, Permutation Importance, or Sequential Feature Selection$)$ and train a logistic regression model with the selected features on the given dataset.

To do so$,$ follow these steps:

Use a wrapper method to select features from the dataset.

Split the dataset into training $(80\%)$ and testing $(20\%)$ sets.

Train a logistic regression model using the training set.

Calculate the accuracy and confusion matrix on the testing set.