dkermany/kaggle_otto

Kaggle: Otto Group Product Classification Challenge

Kaggle Otto Group Product Classification Challenge

My solution that scored 0.42232 and finished Otto competition on 218th position out of 3514 teams.
Represents 1:1 blend of XGBoost model and average of 20 Neural Nets. Models hyper parameters, NN architecture and blend weights have been chosen manually.

Requires:

• XGBoost
• Theano
• Keras, forum link

Other work

Other Kagglers insights I found particularly interesting. For the most part they relate to blending. I list them here for further study:

1. Triskelion. Competition 62nd. Blending
   forum link 1
   forum link 2
   Ensemble Selection from Libraries of Models
   For his turn he is referring to another kaggler Emanuele Olivetti, (forked code)

2. Hoang Duong. Competition 6th. Blending
   forum link
   documentation

3. Adam Harasimowicz. Competition 66th. Blending, Hyperopt
   forked code
   Blog post

4. Mike Kim. Competition 8th. T-SNE features and meta bagging
   forum link
   code