NEURAL-NETWORK-VS-CONV-NETWORK-FEATURE-SELCETION-BINNING
Importing Packages Reading Dataset Dataset Analysis and Prepartion Defining the binary classification column Identifying X and Y Sampling process Since we cannot use '?' when sampling we will convert it temporary to -1 Doing Sampling Process Defining Network and helper function Defining Neural Network Defining Convilutional Neural Network Defining Helper Function Using Neural Network Confusion Matrix Using Convloution Nueral Network Confusion Matix Comments Feature Selection Feature Importance Using top 5 Features Build Neural Network Create CNN Model Using Top 10 Features Creating Neural Network Creating CNN model Using top 15 Features Creating NN Model Creating the CNN Model Using Top 20 Features Creating Neural Network Creating CNN Model Using Top 25 Features Creating Neural Network Creating CNN Model Using all Features Creating Neural Network Evaluating Results Confusion Matrix Feature Binning and Discretization Using pandas qcut functionality to make the transform Feature Importance Using top 5 Features Build Neural Network Create CNN Model Using Top 10 Features Creating Neural Network Creating CNN model Using top 15 Features Creating NN Model Creating the CNN Model Using Top 20 Features Creating Neural Network Creating CNN Model Using Top 25 Features Creating Neural Network Creating CNN Model Using all Features Creating Neural Network Evaluating Results Confusion Matrix COMPARING WITH AND WITHOUT FEATURE BINNING Convolutional Neural Network Evalution Neural Network Evalution
