MDST-FARS-share

This repo is a start where Tiapei Xie, Sheng Yang and Sean Ma are collaborating together for the goal of becoming the top notch Data Scientiest. We started with the the MDST-FARS competition.

Mission:

Helping each other to become the top Data Scientist in our field.

Goals:

We use competitions in Kaggle to sharpen our skill sets. Our main goal is to get placed in the public leader board. Pratical goals for now are:

1. Further test FARS data set with ensemble technologies (Tianpei & Sean).
2. Practice deep learning on FARS data set (Tianpei lead).
3. Continue to learn from 2 public Kaggle competitions (Home Depot; Santander) (Sheng lead).
4. Learn cloud technologies such as AWS (Sean lead).
5. Compete in a public Kaggle competition (maybe in May or June).

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Models and AUC scores:

Model code	Submission CSV	Public Score	Private Score	Note
Model_xgboost-production_weighted.py	fars_submit_xgb004-production_weighted_missing.csv	0.87135	0.86657	No change using missing option
Model_xgboost-production_weighted.py	fars_submit_xgb004-production_weighted.csv	0.87135	0.86657
Model_xgboost-production_weighted_Tian_acc_per.py	fars_submit_xgb005-production_weighted_Tian_acc_per.csv	0.85757	0.85050	Seems like 2 tables with dummies are ok