Quiz 1

Question 1

tasks of classification and prediction as well as pattern discovery

Answer 1

predictive analytics

Question 2

examine unknown categories or predict future

Answer 2

classification

Question 3

predicting value of a numerical variable (ex go up 5%)

Answer 3

prediction

Question 4

designed to find general association patterns between items in large databases, for whole population

Answer 4

association rules/affinity analysis

Question 5

uses individual users’ preferences and tastes given their historic measurable behaviors indicative of preference, for user

Answer 5

collaborative filtering

Question 6

analytical methods in PA

Answer 6

classification, prediction, collaborative filtering

Question 7

process of consolidating a large number of records/cases into a smaller set (rows)

Answer 7

data reduction

Question 8

methods of reducing the number of cases

Answer 8

clustering

Question 9

reducing the number of variables in a set (columns)

Answer 9

dimension reduction

Question 10

what is one of the earliest stages of engaging with data?

Answer 10

exploring it

Question 11

exploration of data by creating charts and dashboards

Answer 11

data visualization/visual analytics

Question 12

used in classification and prediction, must have data available in which the value of the outcome of interest is known (yes/no)

Answer 12

supervised learning algorithms

Question 13

data from which classification or prediction algorithms learns about the relationship between prediction variables and outcome variable

Answer 13

training data

Question 14

data which the algorithm is applied to to test how well it does and fixing any issues

Answer 14

validation data

Question 15

data used for evaluating chosen model

Answer 15

test data

Question 16

used when there is no outcome variable to predict or classify, no learning from when outcome variable is known

Answer 16

unsupervised learning algorithms

Question 17

methods are trained on a set of training data and then their performance is evaluated on a separate set of validation data

Answer 17

data partioning

Question 18

predicted values of training data, they are for the records on which the model was fit

Answer 18

fitted values

Question 19

what does SEMMA stand for?

Answer 19

sample, explore, modify, model, assess

Question 20

nominal categorical variables that have been decomposed into a series of binary variables (yes/no)

Answer 20

dummy variables

Question 21

including all four dummy variables in an algorithm

Answer 21

one-hot encoding

Question 22

knowledge of the particular application being considered, not the algorithm

Answer 22

domain knowledge

Question 23

two ways to standardize data

Answer 23

1. subtract the mean from each value and divide by standard deviation
2. subtract by minimum and divide by range (for 0 to 1 standardization)

Question 24

entire set of operations that was performed on a dataset

Answer 24

workflow

Question 25

maintenance triggered by advance warnings that are predictive of failure

Answer 25

proactive preventive maintenance

Question 26

steps in machine learning process

Answer 26

1. develop understanding of ML project
2. obtain dataset
3. explore, clean, and preprocess data
4. reduce data dimensions if necessary
5. determine ML task
6. partition data (for supervised tasks)
7. choose ML techniques
8. use algorithms to perform task
9. interpret results
10. deploy the model