Comparing regression vs classification in machine learning can sometimes confuse even the most seasoned data scientists. This can eventually make it difficult for them to implement the right methodologies for solving prediction problems. Both regression and classification are types of supervised machine learning algorithms, where a model is trained according to the existing model along with correctly labeled data. But there are also many differences between regression and classification algorithms that you should know in order to implement them correctly and sharpen your machine learning skills. In this blog, we will understand the difference between regression and classification algorithms.<\/p>\n\n\n\n
Some algorithms may need both classification and regression approaches, which is why an in-depth knowledge of both is crucial in the fields of AI and data science<\/a>. Before we deep dive into understanding the differences between regression and classification algorithms. Let’s first understand each algorithm.<\/p>\n\n\n