Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

2.2. XGBoost (Extreme Gradient Boosting) Model The XGBoost algorithm employed in machine learning for regression and classification consists of a series of weak learners (usually decision trees) ...

Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...

The classification of underwater objects into rocks or mines is a vital task in naval security, marine exploration, and environmental studies. The current work introduces a machine learning-based ...

By 2030, it’s expected that the market for streaming data will eclipse $73 billion, growing nearly 20% each year until then. More impressively, the machine learning market—which brought in $15 ...