Question: Suppose you're on a game show, and you're given the choice of three doors: Behind one door is a car; behind the others, goats. You pick a door, say No. 1, and the host, who knows what's behind the doors, opens another door, say No. 3, which has a goat. He then says to you, “Do you want to pick door No. 2?” Is it to your advantage to switch your choice?
http://www.youtube.com/watch?v=QX_oy9614HQ
Cyber Stalking Assignments
Research Clusters - 20 minutes
Red and Black Review
Probability Range
Rule of Addition
Disjoint Events Events A and B are disjoint iff
Conditional Probability
True Bayesians actually consider conditional probabilities as more basic than joint probabilities . It is easy to define P(A|B) without reference to the joint probability P(A,B). To see this note that we can rearrange the conditional probability formula to get:
P(A|B) P(B) = P(A,B)
but by symmetry we can also get:
P(B|A) P(A) = P(A,B)
It follows that:
which is the so-called Bayes Rule.
http://en.wikipedia.org/wiki/Bayesian_network
Remember: Finite State Machines? - Deterministic
Bayes Nets: http://www.idi.ntnu.no/~dingsoyr/diploma/node18.html
Building a k-D tree
Application: 3-D graphics
Algorithm BuildKDTree (S, depth) input: a set of points S, the current depth depth output: the root of a kD-tree storing S if S contains only one point then return a leaf storing this point else if depth is even then Split S into 2 subsets with a vertical line L through the median x-coord else Split, 2 subsets with a horizontal line v_left <- BuildKDTree (S1, depth+1) v_right <- BuildKDTree (S2, depth+1) v <- L return v
Data Classification
Application: Separating Audio Tracks
Audio ML: http://cs229.weebly.com/index.html
ConceptNet
Application: Language
Language ML:
Decision Trees