How I won my second bronze medal on a Kaggle competition

At lunchtime today I was checking my emails and was quite surprised to learn that I have received a bronze medal for the submission I made regarding Kaggle’s August 2021 tabular competition. I have to say this honour was totally unexpected because I only submitted my work to Kaggle the evening previously.

I believe the reason why I won the bronze medal was because I was using a little known feature selection function that is part of the sklearn library of utilities. The post that I wrote on the Kaggle competition that I won the second bronze medal on can be found here if anyone would like to read it:- https://medium.com/mlearning-ai/how-i-improved-my-score-on-kaggles-august-2021-tabular-competition-using-generic-univariate-select-1ef146383d3

The technique that I used to win the bronze medal was sklearn’s GenericUnivariateSelect, which is a type of feature selection. In feature selection, the function performs statistical tests on the features and the output and only the features with high scores are kept.

This is the second bronze medal I have won by competing in Kaggle’s monthly tabular competitions. The post that I wrote on the first bronze medal I received from Kaggle can be found here:- https://medium.com/codex/how-i-won-a-bronze-medal-on-a-kaggle-competition-4abd0424c479