Analytics Vidhya Jantahack Healthcare Analytics

Public Leaderboard Rank: 12

Private Leaderboard Rank: 4

Problem Statement

Data Description at a Glance:

Data after Merging and Feature Engineering:

Description of Approach/Feature Engineering:

1. Created training dataset with outcome column merged with all the camp details.
2. Merged new train dataset and patient dataset to form new train and test dataset
3. Created the train, test dataset with date difference features and also applied encoding on categorical data
4. Created Frequency related features

Tools used

1. Python
2. pandas and numpy libraries for data manipulation
3. sklearn's preprocessing and metrics for evaluating classification models preformance
4. xgboost for gradient boosting

Score

The score obtained using this solution is 0.8398043541

Credits:

This hackathon is repeated after 4 years... also solutions were provided by the previous participants which I referred.
Knocktober 2016

Competition Result

Rank: 12th on public LB and 4th on private LB