Files
ModelTrainEval/figures/pca-spectrum-whitening.mmd
Shaun ZhouandClaude Opus 5 4fc0fa5353 docs: 无监督聚类的数学说明、mermaid 图与 README
- docs/unsupervised-clustering.md: 逐图标准化对仿射光照群的不变性证明、
  多 stage 特征的取舍、PCA 白化失效的谱分析、KMeans 收敛性与 kmeans++ 近似比、
  轮廓系数与 NMI 稳定性的定义、NT-Xent 与 InfoNCE 下界,附全部消融数据与代码对照表
- figures/: 四张 mermaid 图(流水线、KMeans 控制流、SimCLR、主成分谱),
  含 .mmd 源、.md 预览与渲染好的 .png
- README: 数据准备、训练评估、多类/单类、SwanLab、Profiler、聚类与自监督的运行说明

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-09-02 17:55:48 +08:00

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---
config:
xyChart:
width: 1250
height: 520
titlePadding: 16
themeVariables:
xyChart:
titleColor: "#1F2937"
plotColorPalette: "#2563EB, #EA580C"
---
xychart
title "主成分方差谱:白化会把末尾的噪声方向抬到与信号同权"
x-axis "主成分序号 j (PCA 降到 32 维)" [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32]
y-axis "方差占比 (%)" 0 --> 40
bar [38.2, 13.0, 10.8, 6.7, 4.5, 3.6, 3.4, 2.3, 2.0, 1.6, 1.5, 1.3, 1.2, 1.0, 0.9, 0.8, 0.7, 0.7, 0.7, 0.7, 0.5, 0.5, 0.5, 0.4, 0.4, 0.4, 0.3, 0.3, 0.3, 0.3, 0.3, 0.2]
line [3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1]