Significant Improvement in Classification Performance Metrics by Ensemble Approach

机译：集成方法对分类性能指标的显着改进

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摘要

Today most of real time applications are source of big data and classification process over huge amount of this data is a challenge. The training of a single classifier with such type of large amount of data causes plasticity-stability problem. A single classifier is not able to preserve large amount of knowledge when it starts to learn new knowledge. This paper gives the introduction about the ensemble and techniques to generate ensemble which shows that how one can maintain stability between bias and variance to improve classification performance. Various classification performance metrics are elaborated and effect of ensemble size on different evaluation measures is also demonstrated.

机译：如今，大多数实时应用程序都是大数据的来源，而对大量此类数据的分类过程是一个挑战。用这种类型的大量数据训练单个分类器会引起可塑性-稳定性问题。当一个分类器开始学习新知识时，它无法保存大量知识。本文介绍了合奏和产生合奏的技术，它说明了如何保持偏差和方差之间的稳定性以提高分类性能。详细阐述了各种分类性能指标，并展示了合奏大小对不同评估指标的影响。

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《International conference on communications and cyber physical engineering》|2019年|243-249|共7页
会议地点 Pune(IN)
作者
Meenakshi A. Thalor; Veena Bhende; Amrapali Chavan;
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Department of Computer Engineering AISSMS Institute of Information Technology Pune India;

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关键词
Base classifiers; Classification; Classification performance metrics; Ensemble; Evaluation measures;

机译：基本分类器；分类;分类绩效指标；合奏;评估措施;

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1. On viability of detecting malwares online using ensemble classification method with performance metrics [J] . Saranya N., Manikandan V. Computational Intelligence . 2020,第3期

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2. Compensation of feature selection biases accompanied with improved predictive performance for binary classification by using a novel ensemble feature selection approach [J] . Ursula Neumann, Mona Riemenschneider, Jan-Peter Sowa, BioData Mining . 2016,第1期

机译：通过使用一种新颖的整体特征选择方法来补偿特征选择偏差并改善二进制分类的预测性能
3. ACC/AHA classification of care metrics: performance measures and quality metrics: a report of the American College of Cardiology/American Heart Association Task Force on Performance Measures. [J] . Bonow RO, Masoudi FA, Rumsfeld JS, Circulation: An Official Journal of the American Heart Association . 2008,第24期

机译：ACC / AHA护理指标分类：绩效指标和质量指标：美国心脏病学会/美国心脏协会绩效指标工作组的报告。
4. Significant Improvement in Classification Performance Metrics by Ensemble Approach [C] . Meenakshi A. Thalor, Veena Bhende, Amrapali Chavan International conference on communications and cyber physical engineering . 2020

机译：通过集合方法显着改善分类性能指标
5. Performance metrics ensemble for multiobjective evolutionary algorithms [D] . He, Zhenan 2011

机译：多目标进化算法的性能指标集合
6. Compensation of feature selection biases accompanied with improved predictive performance for binary classification by using a novel ensemble feature selection approach [O] . Ursula Neumann, Mona Riemenschneider, Jan-Peter Sowa, 2016

机译：通过使用新颖的集成特征选择方法补偿特征选择偏差并改善二进制分类的预测性能
7. New neighborhood based classification rules for metric spaces and their use in ensemble classification [O] . Mazón López, José Norberto, Micó Andrés, Luisa, Moreno Seco, Francisco 2007

机译：基于新邻域的度量空间分类规则及其在整体分类中的应用

Significant Improvement in Classification Performance Metrics by Ensemble Approach

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