MODE: multiobjective differential evolution for feature selection and classifier ensemble

No abstract is available for this paper.

• Publication year

  2015

• Venue

  Soft Computing - A Fusion of Foundations, Methodologies and Applications

• Publication date

  2015-01-10

• Fields of study

  Medicine, Computer Science

• Identifiers
  DOI 10.1007/s00500-014-1565-5
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Solving Bi-level Problems Using Modified Particle Swarm Optimization Algorithm

  2014cited by this paper
• Machine learning based analysis of gender differences in visual inspection decision making

  2013cited by this paper
• Differential Evolution Based Feature Selection and Classifier Ensemble for Named Entity Recognition

  2012cited by this paper
• Boosting performance of gene mention tagging system by hybrid methods

  2012influential reference
• Weighted Vote-Based Classifier Ensemble for Named Entity Recognition: A Genetic Algorithm-Based Approach

  2011cited by this paper
• Multiobjective optimization for classifier ensemble and feature selection: an application to named entity recognition

  2011cited by this paper
• A multiobjective simulated annealing approach for classifier ensemble: Named entity recognition in Indian languages as case studies

  2011cited by this paper
• Self-adaptive differential evolution algorithm using population size reduction and three strategies

  2011cited by this paper
• Classifier Ensemble Selection Using Genetic Algorithm for Named Entity Recognition

  2010cited by this paper
• Boosting performance of gene mention tagging system by classifiers ensemble

  2010influential reference
• Weighted Vote Based Classifier Ensemble Selection Using Genetic Algorithm for Named Entity Recognition

  2010cited by this paper
• Voice quality conversion using interactive evolution of prosodic control

  2009cited by this paper
• Simplex Differential Evolution

  2009influential reference
• Feature selection techniques for maximum entropy based biomedical named entity recognition

  2009influential reference
• Biomedical Named Entity Recognition Based on Classifiers Ensemble

  2008cited by this paper
• A Simulated Annealing-Based Multiobjective Optimization Algorithm: AMOSA

  2008cited by this paper
• Overview of BioCreative II gene mention recognition

  2008cited by this paper
• High-Recall Gene Mention Recognition by Unification of Multiple Backward Parsing Models

  2007cited by this paper
• Biomedical Named Entity Recognition: A Poor Knowledge HMM-Based Approach

  2007cited by this paper
• BioCreative II Gene Mention Tagging System at IBM Watson

  2007influential reference
• Rich Feature Set, Unification of Bidirectional Parsing and Dictionary Filtering for High F-Score Gene Mention Tagging.

  2007cited by this paper
• ME-based biomedical named entity recognition using lexical knowledge

  2006cited by this paper
• Iterative Feedback Tuning in Fuzzy Control Systems. Theory and Applications

  2006cited by this paper
• Two-Phase Biomedical Named Entity Recognition Using A Hybrid Method

  2005cited by this paper
• Evolutionary computing in manufacturing industry: an overview of recent applications

  2005cited by this paper
• Exploiting Context for Biomedical Entity Recognition: From Syntax to the Web

  2004cited by this paper
• POSBIOTM-NER in the Shared Task of BioNLP/NLPBA2004

  2004cited by this paper
• Introduction to the Bio-entity Recognition Task at JNLPBA

  2004cited by this paper
• Biomedical Named Entity Recognition using Conditional Random Fields and Rich Feature Sets

  2004cited by this paper
• Parallelisation for finite-discrete element analysis in a distributed-memory environment

  2004cited by this paper
• Exploring Deep Knowledge Resources in Biomedical Name Recognition

  2004influential reference
• An Introduction to Variable and Feature Selection

  2003cited by this paper
• A fast and elitist multiobjective genetic algorithm: NSGA-II

  2002cited by this paper
• Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data

  2001cited by this paper
• Feature subset selection using genetic algorithms for handwritten digit recognition

  2001cited by this paper
• Multi-objective optimization using evolutionary algorithms

  2001influential reference
• Multiple Classifier Systems

  2000cited by this paper
• Feature Subset Selection Using a Genetic Algorithm

  1998cited by this paper
• Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces

  1997influential reference
• Feature Selection for Classification

  1997cited by this paper
• Genetic Algorithms in Search Optimization and Machine Learning

  1988influential reference
• An introduction to the statistical analysis of data

  1979influential reference
• A composite classifier system design: Concepts and methodology

  1979influential reference

• Multiobjective Binary Differential Approach with Parameter Tuning for Discovering Business Process Models: MoD-ProM

  2024cites this paper
• A Global-to-Local Evolutionary Algorithm for Hyperspectral Endmember Extraction

  2023cites this paper
• Improved differential evolution with dynamic mutation parameters

  2023cites this paper
• Prediction of stock price movement using an improved NSGA-II-RF algorithm with a three-stage feature engineering process

  2023cites this paper
• A survey of evolutionary algorithms for supervised ensemble learning

  2023cites this paper
• Question Classification in Question Answering System using Combination of Ensemble Classification and Feature Selection

  2021cites this paper
• An ensemble artificial intelligence‐enabled MIoT for automated diagnosis of malaria parasite

  2021cites this paper
• Exploring high-throughput biomolecular data with multiobjective robust continuous clustering

  2021cites this paper
• Feature selection based multivariate time series forecasting: An application to antibiotic resistance outbreaks prediction

  2020cites this paper
• Binary differential evolution with self-learning for multi-objective feature selection

  2020cites this paper
• Burden Surface Decision Using MODE With TOPSIS in Blast Furnace Ironmkaing

  2020cites this paper
• Nature-inspired multiobjective patient stratification from cancer gene expression data

  2020cites this paper
• Cancer molecular subtype classification from hypervolume-based discrete evolutionary optimization

  2020cites this paper
• A multi-objective algorithm for multi-label filter feature selection problem

  2020cites this paper
• A Weighted Voting Classifiers Ensemble for the Brain Tumors Classification in MR Images

  2020cites this paper
• Ensemble Learning via Multimodal Multiobjective Differential Evolution and Feature Selection

  2019cites this paper
• Handwritten Digits Recognition Using an Ensemble Technique Based on the Firefly Algorithm

  2019cites this paper
• Nature-Inspired Multiobjective Cancer Subtype Diagnosis

  2019cites this paper
• Feature Selection for Classification through Population Random Search with Memory

  2019cites this paper
• Multi-objective differential evolution-based ensemble method for brain tumour diagnosis

  2019cites this paper
• Novel multiobjective TLBO algorithms for the feature subset selection problem

  2018cites this paper
• Information theoretic-PSO-based feature selection: an application in biomedical entity extraction

  2018cites this paper
• A methodology for evaluating multi-objective evolutionary feature selection for classification in the context of virtual screening

  2018cites this paper
• Gravitational search algorithm and K-means for simultaneous feature selection and data clustering: a multi-objective approach

  2017cites this paper
• A method with neural networks for the classification of fruits and vegetables

  2017cites this paper
• Robust multiobjective evolutionary feature subset selection algorithm for binary classification using machine learning techniques

  2017cites this paper
• Improving Hotel Room Demand Forecasting with a Hybrid GA-SVR Methodology Based on Skewed Data Transformation, Feature Selection and Parsimony Tuning

  2015cites this paper