Study compares machine learning models of raindrop formation

Raindrops form inside clouds when tiny particles of water collide and stick together, forming larger droplets that eventually ...
Eos

Comparing Machine Learning Models of Raindrop Formation

Better simulations of raindrop formation could help improve climate and weather models. This newsletter rocks. Get the most ...
Lake County Record-Bee

Machine learning helps wildfire forecasts

With peak wildfire season underway in California, PG & E’s Chief Meteorologist Scott Stenfel held a virtual Wildfire Season ...
Aerospace and Mechanical Insider on MSN

AI and machine learning transform materials testing

Materials testing remains a cornerstone of engineering and manufacturing, ensuring that components and structures—from ...
IEEE

A New Method for Learning Decision Trees from Rules

Abstract: Most of the methods that generate decision trees use examples of data instances in the decision tree generation process. This paper proposes a method called "RBDT-1"- rule based decision ...
Investopedia

Decision Trees in Finance: A Tool for Analyzing Risks and Outcomes

Arthur Pinkasovitch, CFA, has worked 5+ years as a financial analyst. He is an associate director at ATB Financial. David Kindness is a Certified Public Accountant (CPA) and an expert in the fields of ...
Microsoft

Decision Forests: A Unified Framework for Classification, Regression, Density Estimation, Manifold Learning and Semi-Supervised Learning

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 tasks. Our model extends ...
Hacker

How To Plot A Decision Boundary For Machine Learning Algorithms in Python

Classification algorithms learn how to assign class labels to examples (observations or data points), although their decisions can appear opaque. A popular diagnostic for understanding the decisions ...
C&EN

Modified Decision Tree with Custom Splitting Logic Improves Generalization across Multiple Brains’ Proteomic Data Sets of Alzheimer’s Disease

V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, Moscow 119334, Russia ...
GitHub

GBDT-MO: Gradient Boosted Decision Tree for Multiple Outputs

Gradient boosted decision tree (GBDT) is a popular machine learning algorithm. Current open-sourced GBDT implementations are mainly designed for single output. When there are multiple outputs, they ...
IEEE

Learning and Application of Different Machine Learning Methods (KNN, SVM, Decision Tree) in Different Datasets

Abstract: With the continuous development of artificial intelligence, machine learning has shown great ability in classification and regression problems. For example, logistic regression, SVM methods, ...