Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and data preprocessing. If you''ve ever built a predictive model, worked on a ...

Abstract: Flood prediction as we known is a important role in reducing the impacts of effective disasters . This paper says that a linear regression-based model is designed for forecasting flood ...

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

Linear regression is the most fundamental machine learning technique to create a model that predicts a single numeric value. One of the three most common techniques to train a linear regression model ...

Abstract: This paper gives an analysis of linear regression using different optimization techniques, including Gradient Descent, Stochastic Gradient Descent, and Mini-batch Gradient Descent. It ...

Quadratic regression extends linear regression by adding squared terms and pairwise interaction terms, enabling the model to capture non-linear structure and predictor interactions. The article ...