Scala and Spark for Big Data Analytics

Unsupervised learning

In unsupervised learning, data points have no labels related with them. Therefore, we need to put labels on it algorithmically, as shown in the following figure. In other words, the correct classes of the training dataset in unsupervised learning are unknown. Consequently, classes have to be inferred from the unstructured datasets, which imply that the goal of an unsupervised learning algorithm is to preprocess the data in some structured ways by describing its structure.

To overcome this obstacle in unsupervised learning, clustering techniques are commonly used to group the unlabeled samples based on certain similarity measures. Therefore, this task also involves mining hidden patterns toward feature learning. Clustering ...