BAN 402 Exam

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Tidymodels framwork ordering

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37 Terms

1

Tidymodels framwork ordering

Recipe, model, workflow

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2

K-fold is used to do

parameter tuning

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3

a logistic regression variable is

yes/no

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4

A linear regression variable is

quantitative, test score, miler per gallon

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5

For a logistic regression model, you look at (blank) on the lefthand side

The log of a particular class

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6

In a logistic regression model you are trying to predict

probability

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7

The process by which a second sample group is given a test to ensure it is applicable to more than one group

Cross validation

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8

What are the k-folds

3, 5, 10

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9

What does cross validation help with

tuning

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10

response variable is categorical, qualitative predicting binary variable, beta is rate "glm"

logistic regression model

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11

In classification, you want AIC to be

low

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12

in classification, you want r squared to be

high

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13

response variable is numerical, quantitative "lm"

linear regression model

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14

confusion matrix

Predictions vs. Actual

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15

developing probabilities/predictions

50% is default threshold, balancing sensitivity and specificity (important in healthcare, credit card fraud, insurance)

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16

splitting data helps with

overfitting

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17

naive accuracy

Confusion Matrix and Statistics: "No Information Rate" and accuracy.. usually w all variables

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18

The r-squared value for a classification model is

AIC

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19

In ROCR, you are looking for

the curve closest to the top left corner

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20

Classification trees use the

rpart package

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21

The parameter to change complexity is

cp

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22

Lower cp means

tree is big

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23

higher cp means

tree is small

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24

A tree with no splits

terminal node

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25

random forest uses

minn and mtry

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26

in clustering, you do not know

dependent variable

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27

in clustering, who specifies the number of clusters

the user

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28

in clustering, you use what function

mbclust

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29

in clustering, what algorithm do you use

kmeans

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30

What does the "CP" parameter control in rpart()?

The complexity of the classification tree

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31

Which function is used to develop predictions from a classification tree in caret?

predict()

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32

What is the term used to describe a tree without any splits?

leaf node

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33

What does the term "min.node.size" control in the ranger function?

The number of observations in a terminal node

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34

Which measure indicates the proportion of true negative instances that are correctly identified by the model?

specificity

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35

What is the key difference between clustering and previous subjects?

dependent variable is unknown

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36

Which package is used to determine the optimal threshold for classification?

ROCR

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37

Which package is used to determine probabilities from logistic regression?

ROCR

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