The Ultimate Unsupervised Learning Quiz: Are You Ready?

Regression

Classification

Clustering

Convolutional Neural Network

Naive Bayes

Decision Trees

Random Forests

K-Means

Classify data

Density based clustering algorithm

Predict future data

Generate new data

Identifying outliers in data

Identifying the center of data clusters

Classifying data

Generating new data samples

Naive Bayes

Decision Trees

Random Forests

Agglomerative clustering

To reduce computational complexity

To reduce overfitting

To improve data visualization

All of the above

Based on nearest neighbors

Based on decision tree splitting

Based on density

Based on distance from centroids

It requires the number of clusters to be known.

It can only handle numeric data.

It is sensitive to outliers.

All of the above.

For classification tasks

For clustering tasks

For dimensionality reduction

For time-series prediction