Grassmann Clustering
Grassmann Clustering
Grassmann Clustering
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n(t)<br />
s(t) �<br />
A<br />
F. Theis<br />
x(t)<br />
has many applications -<br />
for example for<br />
feature extraction<br />
of immunological data<br />
sets<br />
I. Introduction<br />
<strong>Clustering</strong><br />
[ Theis, Hartl, Krauss-Etschmann, Lang. Neural networksignal analysis in immunology. Proc. ISSPA2003. ]<br />
0.426<br />
0.248<br />
0.07<br />
49<br />
35.9<br />
d 22.8<br />
22.1<br />
10.9<br />
d 0.718<br />
53.8<br />
d 4<br />
27.9<br />
9.29 CB(3)<br />
4.44<br />
d 0.0623<br />
CB(3)<br />
ILD(1) CB(1) ILD(2)<br />
ILD(2)<br />
CB(1) CB(1) ILD(2)<br />
ILD(3)<br />
ILD(1) CB(1) ILD(2)<br />
CB(2)<br />
CB(1) CB(1)<br />
ILD(1)<br />
CB(2)<br />
ILD(1)<br />
ILD(1)<br />
ILD(2)<br />
ILD(1) ILD(1)<br />
CB(1)<br />
1.89<br />
1<br />
d 0.166<br />
3.3<br />
1.81<br />
d 0.395<br />
32.1<br />
16.3<br />
d 1.39<br />
5.22<br />
3.28<br />
d 1.35<br />
nO(2)<br />
O(1)<br />
nO(3)<br />
x(1) O(1) x(2)<br />
x(2)<br />
O(1) O(1) x(2)<br />
x(3)<br />
O(2)<br />
nO(1) O(1)<br />
x(1) O(1) x(2)<br />
x(1)<br />
x(1)<br />
x(1)<br />
x(1)<br />
O(2)<br />
x(1)<br />
x(2)<br />
O(1)<br />
13.6<br />
8.23<br />
d 2.8<br />
4.5<br />
1.8<br />
d 0.104<br />
82.6<br />
57.2<br />
d 30.4<br />
699000<br />
446000<br />
d 196000<br />
6<br />
48.1<br />
30.3<br />
d 15.5<br />
37.8<br />
19.1<br />
d 3.2<br />
25.5<br />
16<br />
d 6.84<br />
1.71<br />
1.33<br />
d 1<br />
K−means−Clusters<br />
Apr 6, 2006 :: Tübingen
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