My todays cs607 final paper
Objective:
1.FIND-S
finds the maximally specific hypothesis possible within the version space
2.Learning problem is primarily
composed of three things.
3.Deductive learning working on existing
facts and knowledge
4.In Unsupervised search Given a
set of examples with no labeling, group them into sets called clusters
5.A concept is the representation
of the problem with respect to the given
Attributes
1.Soft-computing
is naturally applied in machine learning applications.
2.Genetic algorithms have been
employed in finding the optimal initial weights of neural
networks.
3.Fact list using command
4.Clips , anything after a
semicolon is a comment
5.Inference networks encode the
knowledge of rules and strategies.
6.Fuzzy sets, unlike classical
sets, do not restrict themselves to something lying wholly in either
set A or in set not-A.
7.The degree of truth that we have
been talking about, is specifically driven out by a function called the membership
function.
8.Output of learning problem in
which phase.
a) Training:
b) Validation
c) Application
d) None
of the given
1.The Candidate-Elimination
algorithm represents the version space by storing only its most general members
(denoted by G) and its most specific members (denoted by S). Given only these
two sets S and G,
2.Drawback of FIND-S, that, it
assumes the consistency within the training set.
3.A linear sequence of steps is
applied repeatedly in an iterative fashion to develop the ES.
4.Predicate logic
and the classical and successful expert systems were limited in that they could
only deal with perfect boolean logic alone.
5.Earlier expert system was known
as
a) Agent
b) Theorem
1.Computer vision
extracts useful information from static pictures and sequence of images.
2.A planning system
can avoid any action that is just not possible at a particular state.
Subjective:
1.Different technologies like fuzzy
logic, GA, ANN. Best suited term?
2.Fuzzy logic deals with reasoning.
Which is fixed n not partial true? Justify yes or no.
3.Probability and fuzzy logics are
same term? Justify your answer’
4.In neural network, Some weak
signal combined into one strong signal. Name best suited term.
5.For robot which condition is
difficult to handle. Ans: Deal with unexpected situation
Q3: which term is best suited
for a situation in which we give a set of example of input/output pairs to find
out a rule that does good job of predicting the out associated with a new input
? 2
Application Testing
• A network is
said to generalize well when the
input-output relationship computed by the network is correct (ornearly so) for
input-output pattern (test data) never used in creating and training the network.
Q5:which term is best suited for
a person who has specialized knowledge, skill and experience in specific area?
give an example form daily life ? 3marks
Expert system
Before we attempt to define an
expert system, we have look at what we take the
term ‘expert’
to mean when we refer to human
experts. Some traits that
characterize experts are:
• They possess specialized
knowledge in a certain area
• They possess experience in the
given area
• They can provide, upon
elicitation, an explanation of their decisions
• The have a
skill set that enables them to
translate the specialized
knowledge gained through
experience into solutions.Try to think of the various traits you associate with
experts you might know, e.g. skin specialist, heart specialist, car mechanic,
architect, software designer. You will see that the underlying common factors
are similar to those outlined above.
Comments
Post a Comment
Please give us your feedback & help us to improve this site.