Classification and Clustering are both integral techniques used in data analysis to categorize objects based on their characteristics. However, they are not the same and have some key differences which we will explore in this article.
Your Total Savings ₹3819 What is Classification in machine learning?
Classification is a kind of supervised machine learning algorithm used to label data. It helps in the projection of the class of the output variable. Binary and Multiclass are two types of classifications.
What is Clustering in machine learning?
Clustering is a kind of unsupervised learning algorithm. It is the collection of objects based on resemblance and distinction between them. It is an approach of collection of objects, so that objects with similar functionalities come together and objects with different attributes move apart.
What are the differences between Classification and Clustering?
Major differences include Classification being a supervised learning method and Clustering being an unsupervised method. Classification uses a training dataset and labels for training data, whereas Clustering does not. Classification is also more complex than Clustering.