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| 2026-09 |
A Comparison of P-Value Aggregation Methods for Feature Importance Testing in Machine Learning |
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| 2026-07 |
Aggregated inference for structural equation modeling with repeated data splitting |
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| 2026-05 |
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| 2025-09 |
A Comparison of Feature Importance Tests in Machine Learning |
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| 2025-08 |
Residual permutation tests for feature importance in machine learning |
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| 2025-08 |
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| 2025-03 |
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| 2024-09 |
Significance Tests for Feature Importance via Python Package Sial |
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說明頁(327) |
| 2024-08 |
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| 2024-07 |
Residual Permutation Tests for Feature Importance in Machine Learning |
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pdf(343) |
| 2024-07 |
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| 2024-01 |
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| 2023-10 |
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| 2023-10 |
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| 2023-10 |
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| 2023-10 |
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| 2023-05 |
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| 2023-01 |
Accelerating Item Factor Analysis on GPU with Python Package xifa |
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| 2022-12 |
Permutation Tests for Testing Variable Importance |
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說明頁(535) |
| 2022-07 |
用JASP完成論文分析與寫作 |
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| 2022-06 |
Accelerating dependency modeling with graphics processing units |
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| 2022-05 |
Usability and effectiveness of adherence monitoring of a mobile app designed to monitor and improve adherence to event-driven and daily HIV pre-exposure prophylaxis among men who have sex with men in Taiwan |
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| 2022-03 |
Penalized Least Squares for Structural Equation Modeling with Ordinal Responses |
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| 2022-03 |
Optimizing Measurement Reliability in Within‑Person Research: Guidelines for Research Design and R Shiny Web Application Tools |
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