IEEE

Soft Gradient Boosting with Learnable Feature Transforms for Sequential Regression

Abstract: We propose a soft gradient boosting framework for sequential regression that embeds a learnable linear feature transform within the boosting procedure. At each boosting iteration, we train a ...
Open Heart

Artificial intelligence-based clustering to identify functional risk phenotypes in heart failure

Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...
Scientific Research Publishing

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ()

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
Visual Studio Magazine

Decision Tree Regression from Scratch Without Pointers or Recursion Using C#

A decision tree regression system incorporates a set of if-then rules to predict a single numeric value. Decision tree regression is rarely used by itself because it overfits the training data, and so ...
Visual Studio Magazine

Linear Regression with Pseudo-Inverse Training Using JavaScript

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 ...
EurekAlert!

Gradient boosting dendritic network for ultra-short-term PV power prediction

Researchers at Central South University in China have developed a new model to improve ultra-short-term photovoltaic (PV) power prediction, as detailed in their publication in Frontiers in Energy. In ...
EurekAlert!

Linking leaf traits to light: A new framework for predicting canopy optical behavior

(A). Light was absorbed by a leaf and reflected and transmitted from the leaf. The reflect light includes specular and diffuse portion, and this reflect light distribution can be modeled with BRDF (B) ...
Hosted on MSN

Linear regression gradient descent explained simply

Understand what is Linear Regression Gradient Descent in Machine Learning and how it is used. Linear Regression Gradient Descent is an algorithm we use to minimize the cost function value, so as to ...
Scientific Research Publishing

Yoon, J. (2020) Forecasting of Real GDP Growth Using Machine Learning Models: Gradient Boosting and Random Forest Approach. Computational Economics, 57, 247-265.

ABSTRACT: The surge of digital data in tourism, finance and consumer markets demands predictive models capable of handling volatility, nonlinear dynamics, and long-term dependencies, where traditional ...
ascopubs.org

Comparative Evaluation of Explainable Machine Learning Versus Linear Regression for Predicting County-Level Lung Cancer Mortality Rate in the United States

Feasibility and Acceptability of Collecting Passive Smartphone Data for Potential Use in Digital Phenotyping Among Family Caregivers and Patients With Advanced Cancer This study applied three ...
ascopubs.org

Comparative Evaluation of Explainable Machine Learning Versus Linear Regression for Predicting County-Level Lung Cancer Mortality Rate in the United States

This study applied three models—random forest (RF), gradient boosting regression (GBR), and linear regression (LR)—to predict county-level LC mortality rates across the United States. Model ...