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In the supervised ML, a machine learns from past data and then produces the desired output [4]. A machine gets its training from already available dataset using appropriate algorithms and inferred function. This inferred function predicts the output and gives an approximate desired result. The used labeled data set helps the algorithm to understand the data and produce the labeled output for more accurate results [5]. Figure 1.2 shows the complete process of supervised learning.

The following are some algorithms which are based on supervised learning:

 • Linear Regression

 • Naive Bayes

 • Nearest Neighbor

 • Neural Networks

 • Decision Trees

 • Support Vector Machines (SVM)

Figure 1.1 Classification of machine learning.

Figure 1.2 Process of supervised learning.