Definition: Classification is a type of supervised learning used when the output variable is a category. It aims to assign input data to one of several predefined classes. Common Algorithms: Logistic ...

This repository contains the capstone project for the IBM "Supervised Machine Learning: Regression" course. The project focuses on developing, training, and evaluating various regression models to ...

if the output values \(y\) are numbers, we call the problem a regression problem. if instead the output values are a small set of values (like ham/spam, or sunny/cloudy/rainy), then we call it a ...

Abstract: Regression in supervised learning often requires the enforcement of constraints to ensure that the trained models are consistent with the underlying structures of the input and output data.

Diagram question answering (DQA), which is defined as answering natural language questions according to the visual diagram context, has attracted attention and has recently become a new benchmark for ...

Supervised machine learning problems are further divided into classification (predicting non-numeric answers, such as the probability of a missed mortgage payment) and regression (predicting ...