I want to design a model to predict gestational age based on the paper. In this process, one way to increase accuracy is feature selection. There are many ways, but I have not obtained the selected features like paper. Also, I could not understand how to extract features based on this paper. In this paper, a bootstrapping procedure and piece-wise regression analysis were used to extract the minimum number of features required for predicting gestational age without compromising predictive power. One hundred bootstrap iterations were performed on the dataset, where 57 samples were drawn randomly and with replacement. Piece-wise regression analysis between the number of features (calculated by applying a range of thresholds to the mean coefficient of each measurement across all bootstrap iterations)
I will appreciate it if you help me to write the codes in Python.