Clustering

Clustering is the type of

• Supervised Learning

• Unsupervised Learning

The goal of clustering to a set of data is to

• divide them into clusters of data that are similar to each other

• predict the class of data

• choose the nearest neighbour cluster

• give a label to each cluster

Which of the following statements are true?

• When dealing with high-dimensional data, we sometimes consider only a subset of the dimensions when performing cluster analysis

• Clustering analysis in unsupervised learning since it requires labeled training data.

• When clustering, we want to put two dissimilar data objects into the same cluster.

• Clustering analysis has a wide range of applications in tasks such as Document analysis, dynamic trend detection, Marketing and sales, and biological network analysis.

Clustering should be done on samples of 300 or more.

• True

• False

Clustering do a division into similar clusters because of the existing labels to the dataset

• TRYE

• FALSE

Ιn the image is depicted :

• K-mean

• DBscan

• Spectral clustering

• Hierarchical clustering