Quiz #1

Question 1

What is the other name of rows?

Answer 1

Instances

Question 2

What are synonyms of column in a dataset?

Answer 2

features, attributes

Question 3

What is the other name for target?

Answer 3

label

Question 4

What process is important to do before running a classifier or ML algorithm? What other processes does it involve?

Answer 4

Preprocessing which includes feature engineering/transformation.

Question 5

Data preprocessing is a form of what three proccesses?

Answer 5

Summarization, Kernelization, and Representation Learning

Question 6

What is the most common way of representing data to a model? What two models require modifications?

Answer 6

Instances and Feautures. Time series and Networks

Question 7

How is data structured in time series

Answer 7

each column is a time slice where instances are a measured property like magnetometer and another row is a pressuremeter.

Question 8

What is an example of numeric type data? How can it be represented to a classifier?

Answer 8

[0.1,3,6,3.4,-34] and it can be represented as-is or normalized.

Question 9

What is an example of binary type data? How can it be represented to a classifier?

Answer 9

[yes,no,no,yes] and it can be represented to a classifier as 0s and 1s.

Question 10

What is an example of ordinal type data? How can it be represented to a classifier?

Answer 10

[advanced,proficient,beginner,advanced], notice it has weight (levels) therefore it can be represented ordered numerically: [3,2,1,3]

Question 11

What is an example of nominal type data? How can it be represented to a classifier?

Answer 11

[josh,pedro,andrea,austin] and it can be represented to the model as one-hot encoded.

Question 12

Where does the target come from in a dataset?

Answer 12

Usually from a feature except in unsuperivsed learning.

Question 13

What do you need to do before optimizing a model?

Answer 13

Understand problem that you are trying to solve and think about features and if they represent or make sense of the problem.