Who leads the classic benchmark?

REL-RWMD k-NN currently leads classic with a score of 96.85 on Accuracy.

What is the state-of-the-art score on classic?

The state-of-the-art result on classic is 96.85 (Accuracy), achieved by REL-RWMD k-NN as of 2019.

How many models are tracked on classic?

Codesota tracks 2 models on classic.

When was the classic leaderboard last updated?

The classic leaderboard on Codesota includes results through 2019.

Codesota · Benchmark · classicHome/Leaderboards/Vision & Documents/Document OCR/classic

Unknown

classic.

Name: classic Benchmark Results
Creator: Unknown
Published: 2019-01-01
License: https://creativecommons.org/licenses/by/4.0/

classic is a state-of-the-art machine learning benchmark indexed on Codesota. This page tracks published model results, top scores per metric, and the SOTA timeline for classic.

Paper ↗Leaderboard ↓

§ 01 · Leaderboard

Results by metric.

Only 2 models on this benchmark

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Accuracy

Accuracy is the reported evaluation metric for classic. Codesota tracks published model scores on this metric so readers can compare state-of-the-art results across sources and model families.

Higher is better

Trust tiers for Accuracyverifiedpapervendorcommunityunverified

Rank	Model	Trust	Score	Year	Links	Fix
01	REL-RWMD k-NN From paper: Speeding up Word Mover's Distance and its variants via properties of distances between embeddings	verified	96.85	2019	Paper ↗Code ↗	Looks wrong?
02	ApproxRepSet From paper: Rep the Set: Neural Networks for Learning Set Representations	verified	96.24	2019	Paper ↗Code ↗	Looks wrong?

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