In the previous article, we have seen what is meant by machine learning and a brief introduction of what are the different processes involved in the working of machine learning. Now in this article, we are going to see what is meant by supervised learning and the types of supervised learning.
What is Supervised Learning?
Supervised Learning is one type of Machine learning. In this, the model is trained and tested with the labelled data. This supervised learning generally learns from the labelled input data and makes out some pretty good accurate results in the form of output data.
Types of Supervised Learning
Supervised Learning is classified into two types. They are
Classification
Regression
Now let's see these types of supervised learning.
Classification
Classification is one of the types of supervised learning which divides or simply classifies a group of things especially present in discrete types of data. Let's see an example of this classification type of supervised learning.
Example:
The classification of emails into a spam or not spam does resemble this classification type of supervised learning where there are discrete numbers of mail present in our mailbox.
Regression
Regression is another type of supervised learning which divides the objects in a way similar to the classification type of supervised learning but the key difference here between the classification and the regression is regression type of supervised learning can be worked with continuous data only. Now let's look into an example that best separates out regression from classification.
Example:
If we take out some continuous values of data like house prices from the past few years of a particular area and we can predict the prices of the houses in the future with the help of those past data. Likewise the prediction or some estimation can be made out from the continuous data in this regression type of supervised learning.
Advantages
There are numerous advantages of this supervised learning. Now let's look at some of them.
Natural Language Processing (NLP)
Recommendation Systems
Object Reorganization
Predictions
Conclusion:
This is all about what supervised learning means and how supervised learning works with different data like continuous and discrete along with the advantages of supervised learning.