One method for dividing data so that data points in the same cluster are as similar as possible and data points in separate clusters are as distinct as possible is clustering analysis.
On the basis of the useful information provided, you must be able to compare the outcomes to existing statistics. Furthermore, the raw data should be quantifiable to facilitate collection and classification. Finally, even when the procedure is used on data sets with similar compositions, they should be repeatable. Getting the right amount of data and sorting it to utilize while creating algorithms is one of the most frequently disregarded problems in predictive modeling. Some estimates place the time spent on this phase by data scientists at 80% of their total time.
Learn more about information here-
https://brainly.com/question/15709585
#SPJ4
