The heart disease prediction model based on Bagging- Fuzzy-GBDT algorithm is composed of Bagging algorithm and fuzzy logic combined with GBDT algorithm. The algo- rithm utilizes the advantage of GBDT is more robust than Decision Tree in over-fitting.
In this paper, we propose a high accuracy integrated prediction algorithm for heart disease diagnosis. The fuzzy logic and Bootstrap Aggregating (Bagging) ...
The fuzzy logic and Bootstrap Aggregating (Bagging) algorithm based on Gradient Boosting Decision Tree (GBDT) algorithm are combined to process heart ...
The GBDT is based on the boosting algorithm, which is one of the ty machine learning algorithms and can be used to solve problems such as classificatio gression ...
This study proposes an Adaptive Neuro-Fuzzy Inference Systems (ANFIS) to diagnose heart disease. Parameters related to membership functions in ANFIS are ...
Dec 25, 2023 · This study presents a novel method combining optimization with ensemble learning techniques, specifically Whale Optimization Algorithm (WOA), with Bagging-GBDT ...
Yuan et al. (2022) presented an AI-Based Heart Disease Prediction Model using the Bagging-Fuzzy-GBDT algorithm, demonstrating high accuracy and privacy ...
This study proposes an Adaptive Neuro-Fuzzy Inference Systems (ANFIS) to diagnose heart disease. Parameters related to membership functions in ANFIS are ...
The main advantage of using this classifier is that it can provide more accurate predictions than many other classifiers since it classifies the input data ...
Dec 9, 2024 · Yuan et al. (2022) presented an AI-Based Heart Disease Prediction Model using the Bagging-Fuzzy-GBDT algorithm, demonstrating high accuracy and ...