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leiyunin/Multi-class-Multi-label-classification-using-SVM

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This project applies SVM classifiers and K-Means clustering to the Anuran Calls (MFCCs) dataset for multi-class, multi-label classification, evaluating techniques like binary relevance, SMOTE, and Classifier Chains to optimize label prediction accuracy.

active 2024-02-282025-02-06 (UTC)

Complete coverage26,499 / 26,499 hourly files (100%) · 2 absent upstream2023-08-152026-08-23 (UTC)
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4
Pushes
1
Pull requests
0
Issues
0
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0
Forks
1

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Line chart, 345 days from 2024-02-28 to 2025-02-06. Pushes: 1 total, peak 1 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.

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Top contributors

Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity

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leiyunin1100

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Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.