In k-means clustering, k represents the a. number of clusters. b. mean of the cluster. c. number of observations in a cluster. d. number of variables.

The correct answer to the question is;

a. number of clusters.

Step-by-step explanation:

Clustering is the process of looking for smaller similar groups of observation within a set of data.

K-means clustering is a vector quantization method used in data mining cluster analysis. The objective of k-means clustering is to a given number of observations into k number of clusters whereby an observation is grouped in a cluster having the closest mean value, hence being representative of tha particular cluster. This is in atempt to make observations in a particular group to be similar.

In k-means clustering, the number of clusters is specified as k.

3/5

step-by-step explanation:

double number line is not a standard concept, so it must have been defined in your textbook. assume top line is numerator.

step-by-step explanation: