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 ...

The Portland Trail Blazers entered the new NBA season hopeful that they would be more competitive on the court. While the team has done that to some extent, they also haven't taken the needed step ...

Abstract: Hyperspectral imaging is a technique that offers detailed chemical or compositional information that is generally not accessible through standard imaging methods like intensity or color ...

Initially designed for continuous control tasks, Proximal Policy Optimization (PPO) has become widely used in reinforcement learning (RL) applications, including fine-tuning generative models. However ...

1 Department of Mathematics, Division of Science and Technology, University of Education, Lahore, Pakistan 2 Department of Mathematics, University of Education, Lahore, Pakistan In this article, a ...

Objectives: 1) Design a KNN algorithm using R, 2) Summarize classification performance using KNN, linear/quadratic regression and Bayes rule. Training and test data are generated from a bi-variate ...

I created an Algorithm in processing to visualize the quadratic regression. But I used gradient descent as a gate way to machine learning.

ABSTRACT: Based on the development of the offshore water drive reservoir, the determination of reasonable water injection of monolayer and single well affects the distribution of remaining oil and ...