Multiclass Classification Algorithms in Machine Learning

When there are only two classes in a classification problem, this is the problem of binary classification, just like that, classification with more than two classes is called multiclass classification. If you want to know the best algorithms for multiclass classification, this article is for you. In this article, I will introduce you to some of the best multiclass classification algorithms in machine learning.

Multiclass Classification Algorithms

Not all classification algorithms in machine learning can perform well in both the problems of binary and multiclass classification. Some algorithms are best to use in binary classification problems, while some are best to use in multiclass classification problems. Only some of them like decision trees can be used in both multiclass and binary classification problems. So below are some of the best multiclass classification algorithms in machine learning that you should know:

  1. Multinomial Naïve Bayes: The multinomial Naïve Bayes algorithm is one of the variants of the Naïve Bayes classifiers in machine learning that is perfect to use in the problems of multiclass classification. One of the advantages of using this algorithm is that it easily handles large datasets. So you can always prefer this algorithm while working on multiclass classification problems.
  2. Decision trees: The decision tree algorithm can predict both categorical values and actual values. With the ability to predict categorical values, it not only works well on binary classification problems but also on multiclass classification problems. One of the advantages of using decision trees is that you can use this algorithm without normalizing your dataset.
  3. K Nearest Neighbor: K Nearest Neighbor is one of the machine learning algorithms that can be used for classification, but it is generally not preferred for classification problems because there are so many algorithms already out there that are easier to use and understand. But one of the advantages of the KNN algorithm over other classification algorithms is that it can be used for multiclass classification problems.

Summary

So Multinomial Naïve Bayes, Decision trees, and KNN are some of the best machine learning algorithms that can be used for multiclass classification problems. When there are only two classes in a classification problem, this is the problem of binary classification, just like that, classification with more than two classes is called multiclass classification. I hope you liked this article on multiclass classification algorithms in machine learning. Feel free to ask your valuable questions in the comments section below.

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Aman Kharwal
Coder with the ♥️ of a Writer || Data Scientist | Solopreneur | Founder
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