ML_Kaggle_Titanic

Why

The main reason for doing this is to compare building an ML model in C#/.NET vs Python.

Overview

This is a project to predict the survival of passengers on the Titanic.

The dataset is from Kaggle and the goal is to predict whether a passenger survived or not.
The dataset contains 891 rows and 12 columns.

Comparison of LightGBM and FastTree and a deep learning ensemble model consisting of:

SDCA Logistic Regression
FastForest
LBFGS Logistic Regression

Usage of Nvidia GPU for training also tested, although on this trivial amount of data it is not needed.

Example Output

Model Comparison Results:  
Model Type           Accuracy        AUC             F1 Score        Training Time   
Standard LightGBM    0.8799          0.9585          0.8366          0.20s
FastTree             0.8878          0.9604          0.8471          0.21s  
Deep Learning        0.9910          0.9999          0.9883          0.88s