Week 11 - Data Mining (Clustering and Association)

Question 1

What is clustering and association used for?

Answer 1

when we don’t want to predict variables

Question 2

What is clustering?

Answer 2

natural grouping of data based on similarities and differences in

Question 3

What is needed to interpret and label clustered data?

Answer 3

human

Question 4

What is involved in the algorithm k-mean?

Answer 4

assigns each data point to cluster who’s center is nearest

Question 5

What does k stand for in k-mean?

Answer 5

predetermined number of clusters

Question 6

What is k-means weakness

Answer 6

requires predetermined k and only works with numerical data

Question 7

What is association?

Answer 7

finds the common co-occurrence of things

Question 8

What is involved in the algorithm apriori?

Answer 8

finds subsets that are common to at least a minimum number of itemset (support threshold)

Question 9

What are the two main data types

Answer 9

-qualitative
-quantitative

Question 10

What are the qualitative data types

Answer 10

-nominal
-ordinal

Question 11

What are the quantitative data types

Answer 11

-discrete
-continuous

Question 12

What is nominal data

Answer 12

label data that does not have an order

Question 13

What is ordinal data

Answer 13

label data that has an order

Question 14

What is discrete data

Answer 14

numbered data that are integer or whole number

Question 15

What is continuous data

Answer 15

numbered data in the form of fractional numbers