feature-selection-codes
Aim of this code to adapt the Levenberg Marquardt Algorithm via a continuous feature selection technique. The method relies on the use of structured l2 penalty. The implementation is done by adapting the gradient descent algorithm in TensorFlow. Data preparation was performed via unsupervised learning (clustering, normalization, imputation and feature ranking), correlation; while training involves adapted Deep learning using Feed-forward Artificial Neural Networks.