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首页> 外文期刊>International Journal of Innovative Computing Information and Control >A NEW ALGORITHM OF ENSEMBLE LEARNING FOR MEDICAL KNOWLEDGE-BASED SYSTEMS AND KNOWLEDGE-BASED SYSTEMS: HYBRID BAYESIAN COMPUTING (MULTINOMIAL LOGISTIC REGRESSION CASE-BASED C5.0-MIXED CLASSIFICATION AND REGRESSION TREE)
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A NEW ALGORITHM OF ENSEMBLE LEARNING FOR MEDICAL KNOWLEDGE-BASED SYSTEMS AND KNOWLEDGE-BASED SYSTEMS: HYBRID BAYESIAN COMPUTING (MULTINOMIAL LOGISTIC REGRESSION CASE-BASED C5.0-MIXED CLASSIFICATION AND REGRESSION TREE)

机译：基于医学知识的系统和基于知识的系统的可学习的新算法：混合贝叶斯计算（基于多项式回归案例的C5.0混合分类和回归树）

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摘要

This paper attempts to answer the question "How to construct and apply the novel algorithm based on Ensemble Learning approach called Bayesian Mixed Probability Distributions-CBR-C5.0-CART for Medical Knowledge-Based Systems and Knowledge-Based Systems (KBSs)?" The finding of this study is the new algorithm of Bayesian-Mixed Probability Distributions-C5.0-CART which is developed for the inference engines of KBSs. The proposed algorithm is applied to Thalassemia data set including F-cell, HbA_2, and Inclusion Body of Thalassemia patients. These are collected from medical practitioner and scientist who are the experts in Thalassemia diagnosis. In the future, this algorithm and a new collected data set will be combined with graph theory to generate the new theory called Ramsey Graph Bayesian-Mixed Probability Distributions for Digital Images Processing and Images Processing.
机译：本文试图回答以下问题：“如何构建和应用基于贝叶斯混合概率分布-CBR-C5.0-CART的基于集成学习方法的新颖算法，以用于基于医学知识的系统和基于知识的系统（KBS）？”这项研究的发现是针对KBS推理引擎开发的新贝叶斯混合概率分布C5.0-CART算法。该算法应用于地中海贫血患者的F细胞，HbA_2和地中海贫血患者的包涵体数据集。这些是从地中海贫血症诊断专家的医生和科学家那里收集的。将来，该算法和新收集的数据集将与图论结合，以生成称为数字图像处理和图像处理的拉姆西图贝叶斯混合概率分布新理论。

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