I need the code for this and some explanations, please!

Use the Iris data from sklearn.

1. Using the whole dataset (without splitting it into two as train and test sets), calculate the F1 values.

2. If a regularization model is used such that it aims to maximize an updated version of F1 score: F1_Score_Updated = F1_Score + 0.1*[Number of explanatory variables], determine the best model and report which variables should be included in the best model.