Supervised Learning | Unsupervised Learning |
Deals with known and labelled data | Deals with unknown and unlabeled data |
Input variables and output variables are specified | Only input data are specified |
The ultimate goal is to determine the function so well that when new input dataset is given, then it can predict the output | The ultimate goal is to find the hidden patterns or underlying structure in the given input data in order to learn about the data |
Uses training data to learn a relationship between the input and the outputs | Does not use output data |
It is a Predictive Modeling technique which predicts the future outcomes | It is a Descriptive Modeling technique which explains the hidden relationship between the data elements |
More accurate results are obtained as input data and corresponding output are well known, and the software only needs to give predictions | Less accurate results are obtained as the input data are unlabeled. Thus, the software has to first understand and label the data and then give predictions |
Learning method takes place offline | Learning method takes place in real time |
It includes classification and regression algorithms | It includes clustering and association algorithms |
Complex in Computation | Less Computational Complexity |