Comparison of 2D embedding methods for visualizing cluster distributions and segment-wise feature values.

<p>(A) Columns (left to right): (1) Supervised UMAP (S-UMAP), incorporating both feature values and cluster identities; (2) Unsupervised UMAP using only feature values; (3) S-UMAP with shuffled cluster identities; and (4) t-SNE projection based on feature values (early_exaggeration = 12, perpl...

Olles dieđut

Furkejuvvon:

Bibliográfalaš dieđut
Váldodahkki:	Romain Fayat (22404831) (author)
Eará dahkkit:	Marie Sarraudy (22404834) (author), Clément Léna (620337) (author), Daniela Popa (645591) (author), Pierre Latouche (4249681) (author), Guillaume P. Dugué (17560534) (author)
Almmustuhtton:	2025
Fáttát:	Genetics Neuroscience Biotechnology Cancer Science Policy Biological Sciences not elsewhere classified Information Systems not elsewhere classified subtle motor changes rodent neurophysiological devices providing unparalleled access parkinson &# 8217 inertial time series include orienting movements imposes environmental constraints computationally efficient change based probabilistic clustering unbiased behavioral analysis order behavioral structures view video tracking minimal computational cost elementary components remains candidate behavioral motifs statistically homogeneous segments behavioral phenotyping video recordings identified motifs grooming components computational neuroethology unsupervised framework point detection pipeline detects olfactory exploration motif sequence methodology offers limited scalability induced dyskinesia easily scalable current standard commonly integrated central challenge body kinematics
Fáddágilkorat:	Lasit fáddágilkoriid Eai fáddágilkorat, Lasit vuosttaš fáddágilkora!

Comparison of 2D embedding methods for visualizing cluster distributions and segment-wise feature values.

Geahča maid