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