Weekly Quiz 1

True

False

Binary Classification

Multi-class multilabel

Single class multilabel

Multi-class Single Label

Representation Learning

Classification

Regression

F1 Score

AUC

Predicted vs True Chart

Precision

Classification

Association

Unsupervised Learning

Multiclass Classification

Historical weather data.

The process of the algorithm examining a large amount of historical weather data.

Learning Rate

Performance measure

training data (70%), test data (10%), validation data (20%)

training data (50%), test data (20%), validation data (30%)

test data (70%), training data (10%), validation data (20%)

test data (20%), training data (70%), validation data (10%)

Increase in K will result in higher time required to cross validate the result.

Higher values of K will result in higher confidence on the cross-validation result as compared to lower value of K.

If K=N, then it is called Leave one out cross validation, where N is the number of observations.

Less than 100 seconds

100 – 300 seconds

Can’t estimate

More than or equal to 600 seconds

None of the above

Accuracy is ~0.91

Misclassification rate is ~ 0.91

False positive rate is ~0.95

True positive rate is ~0.95