Supervised learning can be expressed in real life as Learning Under the Supervision of Someone. In machine learning terms we can say that machine is learning based on some data. It is used when we have some sort of input and we want to predict the output based on some dataset. Training data or labeled data is some sort of supervisor for the machine which is giving instructions to the machine. Training data or labeled data has both input and output.
Let’s first take an example that we have data on cancer germs and we are predicting that cancer is malignant or benign. We already have a data set of the cancer patients which is labeled for malignant and benign. The machine will apply different algorithms (we’ll talk later about them) and develop a model for the cancer patients. When there will be a new cancer patient the machine will predict the cancer type with malignant or benign based on the previous data set.
Therefore, supervised learning will make the machine intelligence to predict the cancer type based on the dataset we have provided to the machine. The more the dataset is refined the more accurate will be the results.