BACHELOR OF BUSINESS ADMINISTRATION

Detailed explanation-1: -We can think of unsupervised learning problems as being divided into two categories: clustering and association rules. Clustering is an unsupervised learning technique, which groups unlabeled data points based on their similarity and differences.

Detailed explanation-2: -Data mining techniques come in two main forms: supervised (also known as predictive or directed) and unsupervised (also known as descriptive or undirected). Both categories encompass functions capable of finding different hidden patterns in large data sets.

Detailed explanation-3: -Data Mining is performed on certain data sets by humans to find interesting patterns between the items in the data set. Data Mining uses techniques created by machine learning for predicting the results while machine learning is the capability of the computer to learn from a minded data set.

Detailed explanation-4: -Unsupervised learning, also known as unsupervised machine learning, uses machine learning algorithms to analyze and cluster unlabeled datasets. These algorithms discover hidden patterns or data groupings without the need for human intervention.