Unsupervised learning
-constructure
density estimation
-clustering
-dimensionality reduction
blind separation
K Means Clustering
– need to know k
– local minimum
– high dimentionality
– lack of mathematics
Gaussian Learning
pacamakes of a gaussian
f(x1u102)=1/√2πΘ exp(x-μ)2/2α2
μ=1/m mΣj=1 xg
Data x1…xm p(x1…xm|μ1Θ2)=πi f(xi|μ1Θ2)=(1/2πΘ2)m/2 exp – Σπ(xi-μ)2/2α2
m/2 log 1/2πα2 – 1/2α2 mΣi=i(xi-μ)2
