Date post: | 03-Apr-2019 |
Category: |
Documents |
Upload: | trinhthien |
View: | 221 times |
Download: | 0 times |
Web Science & Technologies
University of Koblenz ▪ Landau, Germany
Data Mining & Machine Learning
Dipl.-Inf. Christoph Carl Kling
C. C. Kling NetHDP3 of 17
WeST
Probability Theoryn = 1 n >= 1
Bernoulli = Binomial for n = 1 Binomial
k = 2
k > 2
Multinomial
100
1
Multinomial for n = 1
p
n → ∞
Gaussian
MulivariateGaussian
1 2 3 k
p
number of successes
C. C. Kling NetHDP4 of 17
WeST
Experiment
Observations c (our Data)Hidden (latent) parameter p
Example: tossing a coin: 2 x head, 0 x tail
tail head
C. C. Kling NetHDP8 of 17
WeST
Probabilistic models
p more likely is close to 0.5!
Prior probability
C. C. Kling NetHDP15 of 17
WeST
Parameter Estimation
Maximum a posteriori estimation (MAP)
Bayesian inference
C. C. Kling NetHDP16 of 17
WeST
Parameter Estimation
Maximum a posteriori estimation (MAP)
Bayesian inference