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Classification Error Rate on UCI Htru2

Classification Error Rate on UCI Htru2

1.93Error RateGPnn

Updated 5mo ago

Evaluation results

Method	Links
GPnn2026.05		1.93
Var2026.05		1.93
FM-GP2026.05		1.96

State-of-the-art paper

GPnn

Leveraging Locality and Robustness to Achieve Massively Scalable Gaussian Process Regression

Dataset

UCI Htru2

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Related benchmarks

Classification on MNIST (Error Rate, ECE)Classification on CIFAR10 (Error rate, ECE)Training Time on UCI Eeg Classification on UCI Htru2 Classification on UCI Letter

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