Learning Ranking for Horse Racing Prediction

1st Problem: Data Table and Processing

1st Problem: Data Table and Processing

The pre-processing in data table including

  • Missing data
  • Categorical data
  • Numerical data

=> How can we solve it when data is missed?

Solution for 1st Problem:

There are a huge number of encoding method. However, what is the most relevant to your model?

Solution for 1st Problem

  • Ordinal
  • One-Hot
  • Binary
  • Frequency
  • Hashing
  • Helmert
  • Backward Difference
  • Target
  • Leave One Out
  • Weight Of Evidence
  • James-Stein
  • M-estimator

However, it always worth tries all the techniques that apply to the feature and decides which one works best for your model.

2nd Problem: Ranking in Competition

2nd Problem: Ranking in Competition

For some of competitions and advertisements, the ranking results are central parts of many information retrieval problems, such as document retrieval, collaborative filtering, online advertising and racing competition. We can consider the experimental in the figure such as ranking problem for Horse Racing.

Solution for 2nd Problem

Solution for 2nd Problem

For this problem, we use the technical algorithms named

  • XGboost Ranking
  • LightGB Ranking
  • CatBoost Ranking

for solving.

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