11) Probability (paper and pencil --- 7 points)
Textbook problem 14.4
12) Bayes Theorem (paper and pencil --- 5 points)
a)The following predicates are given:
Rain:= "It will rain tommorow"
Cloudy:= "The sky is cloudy today"
Humid:= "It is humid today"
Cold:= "it is cold today"
Moreover, P(Rain)= 0.1 P(Cloudy|Rain)=0.8 P(Humid|Rain)=0.9 P(Cold|Rain)=0.2 P(Cloudy)=0.6 P(Humid)=0.8 P(Cold)=0.4
Will it (usually) rain tomorrow --- compute:
$P(Rain|Cloudy and Humid and Cold) and
P(Rain|Cloudy and Humid)
b) Bayes's theorem is usually applied making the so called conditional indepence. Explain the assumption by referring to the example a (explain what what was assumed to be independent in your solution of problem a).
14) Belief Networks --- Getting the Numbers right! (Belief Network Development &
Constraint Satisfaction -- 52 Points)
Assume a belief network with a particular structure is given for
Huntington disease. Furthermore the following constraints have
been provided (for details see
Wordfile that contains
the network structure and the constraints;
Wordfile with Constraints of HD-GBBN only) with
respect to the assumed belief network structure. This
knowledge has been been obtained through extraction from
Disease Profile and through interviewing
domain experts. Provide probability tables for the given
belief network structure
(using Netica or any other belief network tool) that implements those
Submit the results of running your belief network for the
a) nothing is known
b) patient has Chorea
c) test showed CAG-repeat is 44
d) test showed CAG-repeat of 60 and psychiatric disturbances
e) patent has psychiatric disturbances and abnormalities in Cognition
f) patient has positive family history and has been symptom free and is 48 years old.
Write a 1-page report that briefly discusses how you solved the problem. In summary, you submit a 1-page report, your belief network, and the answers your belief network provided for questions a-f
15) RETE Algorithm (Paper and Pencil ---- 19 points)
a) Give the RETE-network for the following CLIPS-rule (there was a line cut of in b); the changed part is red color):
(defrule Santa (P ?x ?y 2) (Q ?y 3) (R ?x 3 ?z) => ...)
16) Decision Trees (Paper and Pencil --- 14 points)
Construct the decision tree C4.5 would generate for the following dataset (updated on Nov. 19, 1999):
17) Knowledge Discovery using Decision Trees (using a decision tree tool, learning about data analysis and knowledge discovery --- 66 points) The goal of this project is to explore how decision tree tools can help in predicting
18) Ontologies (18 points)
Read the Chadrasekaran&...'s article centering on ontologies, and write a 150 word essay that addresses most of the following questions and topics (you are allowed to skip one or two questions/topics): What reasons does the author give why ontologies are important? Do you agree with what the author is saying? Is the list of reasons that the author gives, complete (if no, give other reasons not listed in the paper). Give a list of applications for which ontologies are/might become important --- also briefly discuss what role ontologies play in the context of the listed applications. What kind of ontology tools / ontology technologies are needed to support these applications?