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Flashcards in Module 3 Deck (9)
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1
Q

What is Confusion Matrix?

A

Performance measurement for machine learning classification

2
Q

Logistic regression?

A

Outputs probabilities
if P > 0.5 = Data is 1
If P < 0.5 = Data is 0

3
Q

Linear Regression?

A

Choosing parameters

4
Q

Ridge/Lasso Regression?

A

Choosing alpha

5
Q

K-Nearest Neighbors?

A

Choosing n_neighbors

6
Q

Parameters like alpha and k?

A

Hyperparameters

7
Q

Choosing the correct hyperparameter?

A

Different hyperparameter values
Fit all of them separately
Essential to use cross-validation

8
Q

Why scale data?

A

Many models use some form of distance to inform them

Features on larger scales can unduly influence the model

9
Q

Ways to normalize the data?

A

Standardization - subtract the mean and divide by variance