English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This article discusses in detail the rating system that won the kagglecompetition "Chess Ratings: Elo vs the rest of the world". The competitionprovided a historical dataset of outcomes for chess games, and aimed todiscover whether novel approaches can predict the outcomes of future games,more accurately than the well-known Elo rating system. The winning ratingsystem, called Elo++ in the rest of the article, builds upon the Elo ratingsystem. Like Elo, Elo++ uses a single rating per player and predicts theoutcome of a game, by using a logistic curve over the difference in ratings ofthe players. The major component of Elo++ is a regularization technique thatavoids overfitting these ratings. The dataset of chess games and outcomes isrelatively small and one has to be careful not to draw "too many conclusions"out of the limited data. Many approaches tested in the competition showed signsof such an overfitting. The leader-board was dominated by attempts that did avery good job on a small test dataset, but couldn't generalize well on theprivate hold-out dataset. The Elo++ regularization takes into account thenumber of games per player, the recency of these games and the ratings of theopponents. Finally, Elo++ employs a stochastic gradient descent scheme fortraining the ratings, and uses only two global parameters (white's advantageand regularization constant) that are optimized using cross-validation.

How I won the "Chess Ratings - Elo vs the Rest of the World" Competition