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Flashcards in Analytic Techniques Deck (110)
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31

what does regression do?
a) looks at a variable between inputs and the outcome
b)looks at the relationship between a set of variables and the outcome
c) looks at the relationship between a set of outputs

b)looks at the relationship between a set of variables and the outcome

32

what is linear regression

used to estimate a continuous value as linear

33

in regression, what does OLS stand for?

Ordinary least squares

34

in regression, what does OLS do?

finds the best fit line

35

what is the p-value in regression?
a)p-value can be used to look for numeric input values
b)p-value can be used to determine if the coefficient is significantly not different than zero.
c)p-value can be used to determine if the coefficient is significantly different than zero.

c)p-value can be used to determine if the coefficient is significantly different than zero.

36

what does a large p-value mean?
a) null hypothesis is rejected
b) null hypothesis is not rejected

b) null hypothesis is not rejected

37

what are residuals in regression?
a)the similarities between the observed and the estimated outcomes
b)the differences between the observed and the estimated outcomes

b)the differences between the observed and the estimated outcomes

38

what is logistic regression?

used to estimate the probability that an event will occur (probability borrower will default)

39

what can logistic regression also be considered as?

classifier

40

what is the standard threshold of logistic regression?

0.5 (50%)

41

What is the preferred method for binary classification problems?

Logistic regression

42

Which isnot binary classification problems?
A)true/false
B)approve/deny
C)respond to medical treatment/not response
D)confidence/lift

D) confidence/lift

43

what does pseudo-r2 mean?
a)deviance/null deviance
b)r squared
c)square root

a)deviance/null deviance

44

what is naive Bayes?

determine the most probable class label for each object

45

what is naive Bayes based on?

Bayes law

46

what is naive Bayes used for?
a)spam filtering
b)scoring
c)fraud
d)text analysis

spam
fraud

47

what is this?
P(C | A)*P(A) = P(A | C)*P(C) = P(A ^ C).

bayes law

48

to build the naive Bayes classier what do you need?

probability of all class labels

49

in naive Bayes how to classify something?

work out the probability total (good/bad) then multiply all good together and times by total

50

what is a confusion matrix

TPR/FPR

51

where are decision trees found?

data mining applications

52

what are the two types of decision trees?

classification trees
regression trees

53

what is a classification tree?

segment observations into homogeneous groups

54

what is a regression tree?

variations of regression and the average value of each node is returned

55

what is a branch of decision tree?

outcome of decision

56

what is an internal node of decision tree?

test points

57

what is a leaf node of a decision tree?

end of the last branch

58

what should you use a decision tree?

when if-then is preferred to a linear model

59

what is a weak learner (decision trees)

short decision tree

60

in decision trees how do you get the most informative attribute?

entropy based methods