Weka 贝叶斯网络实践教程

Bayesian networks practice

(Weka)

Weather data

What is the Bayesian Network

corresponding to Naïve Bayes?

“Effects” and “Causes” vs. “Evidence” and “Class”

•

Why Naïve Bayes has this graph?

P(Humidity=High | play=yes) *

P(Windy=True | play=yes) *

P(play=yes) / P(E)

we are interested in computing

P(…|play=yes), which are

probabilities of our evidence

“observations” given the class.

•

Of course, “play” isn’t a cause for

“outlook”, “temperature”,

•

For example, if play=yes, and we

know that the playing happens

indoors, then it is more probable

(than without this class information)

the outlook to be observed “rainy.”

whose induced classifier might have estimated error (through cross-

validation) better or worse than the Naïve Bayes one (depending on

the data).