Machine Learning
About
This chapter gives an overview of the core concepts of machine learning (ML) -- the use of algorithms that learn from data, identify patterns, and make predictions or decisions without being explicitly programmed -- that are relevant to particle physics with some examples of applications to the energy, intensity, cosmic, and accelerator frontiers.
Javier M. Duarte, Uros Seljak, Kazu Terao• 2025
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Image Classification | PatternNet | Accuracy95.61 | 48 | |
| Image Classification | EuroSAT MSI | Overall Accuracy (OA)94.69 | 14 | |
| Image Classification | UC Merced | Overall Accuracy (OA %)75 | 14 | |
| Classification | Corners | Accuracy98.33 | 6 | |
| Classification | Half Kernel | Accuracy95 | 6 | |
| Classification | Two Spirals | Accuracy90.83 | 6 | |
| Classification | Crescent Moon | Accuracy97.5 | 6 | |
| Classification | Cluster-in-Cluster | Accuracy94.17 | 6 | |
| Classification | Outliers | Accuracy98.33 | 6 |
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