A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning ...

This project focuses on Predictive Maintenance for industrial equipment using machine learning. The goal is to predict potential machine failures before they occur, enabling proactive maintenance and ...

Abstract: The Versatile Video Coding (VVC) standard notably enhances encoding efficiency with the Quad-Tree plus MultiType Tree (QTMTT) partition structure. However, the complex QTMTT tool presents ...

The decision tree that Zeldman linked to has five questions: Does the image contain text ... In a world ruled by algorithms, SEJ brings timely, relevant information for SEOs, marketers, and ...

Definition: Decision tree analysis involves making a tree-shaped diagram to chart out a course of action or a statistical probability analysis. It is used to break down complex problems or branches.

Researchers used machine learning models to predict preterm birth risk, identifying linear SVMs as the most accurate, with ...

To solve these problems, this paper proposes a reservoir operation scheme decision-making model IWGAN-IWOA-CNN based on artificial intelligence and deep learning technology. In view of the lack of ...

The research object of this paper is PWD tree, by increasing the flying height of UAV, increasing the field of view range of the camera, increasing the number of image targets, and based on this, a ...

This review presents a unified, efficient model of random decision forests which can be applied to a number of machine learning, computer vision, and medical image analysis ... Proposing new algorithms ...

The mathematics behind artificial intelligence (AI) and machine learning (ML) rely on linear algebra, calculus, probability, ...