Supervised Machine Learning—Classification
Classification and prediction are two important methods of data analysis used to find patterns in data. Classification predicts the categorical class (or discrete values), whereas regression and other models predict continuous valued functions. For example, a classification model may be built to predict the results of a credit-card application approval process (credit card approved or denied) or to determine the outcome of an insurance claim. Many classification algorithms have been developed by researchers and machine-learning experts. Most classification algorithms are memory intensive. Recent research has developed parallel and distributed processing architecture, such as Hadoop, which is capable of handling large amounts of data.