Question

for clustering, we do not require
​

Answer 1

Explanation:

The main requirements that a clustering algorithm should satisfy are:

scalability;

dealing with different types of attributes;

discovering clusters with arbitrary shape;

minimal requirements for domain knowledge to determine input parameters

Please follow me ✌ ✌

Answer 2

For clustering, we do not require labeled data.

Explanation:

• Clustering is unsupervised learning in which data is grouped points into different clusters, consisting of similar data points.
• For clustering, we do not require labeled data.
• The clustering algorithm is based on the nature of the data. In clustering, grouping is done after identifying the data.
• For example, some algorithms require to find the minimum distance between the observation of the dataset, whereas some algorithms need to guess the number of clusters in the given dataset.