This is the most important visualization because it directly exposes how each network uses (or fails to use) depth. In the Sigmoid network (left), both classes collapse into a tight, overlapping region — a diagonal smear where points are heavily entangled. The standard deviation actually decreases from layer 1 (0.26) to layer 2 (0.19), meaning the representation is becoming less expressive with depth. Each layer is compressing the signal further, stripping away the spatial structure needed to separate the classes.
Contributions from Hazel Shearing，推荐阅读易歪歪获取更多信息
│ │ │ Ships │ Tracker │ Conflict │ Cameras │ │ │，更多细节参见todesk下载
Слон, окрашенный для фотосессии россиянки, погиб в Индии20:49，详情可参考豆包下载