Immune centroids oversampling method for binary classification.

Abstract:

:To improve the classification performance of imbalanced learning, a novel oversampling method, immune centroids oversampling technique (ICOTE) based on an immune network, is proposed. ICOTE generates a set of immune centroids to broaden the decision regions of the minority class space. The representative immune centroids are regarded as synthetic examples in order to resolve the imbalance problem. We utilize an artificial immune network to generate synthetic examples on clusters with high data densities, which can address the problem of synthetic minority oversampling technique (SMOTE), which lacks reflection on groups of training examples. Meanwhile, we further improve the performance of ICOTE via integrating ENN with ICOTE, that is, ICOTE + ENN. ENN disposes the majority class examples that invade the minority class space, so ICOTE + ENN favors the separation of both classes. Our comprehensive experimental results show that two proposed oversampling methods can achieve better performance than the renowned resampling methods.

journal_name

Comput Intell Neurosci

authors

Ai X,Wu J,Sheng VS,Zhao P,Cui Z

doi

10.1155/2015/109806

subject

Has Abstract

pub_date

2015-01-01 00:00:00

pages

109806

eissn

1687-5265

issn

1687-5273

journal_volume

2015

pub_type

杂志文章
  • Designs and Algorithms to Map Eye Tracking Data with Dynamic Multielement Moving Objects.

    abstract::Design concepts and algorithms were developed to address the eye tracking analysis issues that arise when (1) participants interrogate dynamic multielement objects that can overlap on the display and (2) visual angle error of the eye trackers is incapable of providing exact eye fixation coordinates. These issues were ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2016/9354760

    authors: Kang Z,Mandal S,Crutchfield J,Millan A,McClung SN

    更新日期:2016-01-01 00:00:00

  • Study on the calculation models of bus delay at bays using queueing theory and Markov chain.

    abstract::Traffic congestion at bus bays has decreased the service efficiency of public transit seriously in China, so it is crucial to systematically study its theory and methods. However, the existing studies lack theoretical model on computing efficiency. Therefore, the calculation models of bus delay at bays are studied. Fi...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/750304

    authors: Sun F,Sun L,Sun SW,Wang DH

    更新日期:2015-01-01 00:00:00

  • Image-Guided Rendering with an Evolutionary Algorithm Based on Cloud Model.

    abstract::The process of creating nonphotorealistic rendering images and animations can be enjoyable if a useful method is involved. We use an evolutionary algorithm to generate painterly styles of images. Given an input image as the reference target, a cloud model-based evolutionary algorithm that will rerender the target imag...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/4518265

    authors: Wu T

    更新日期:2018-02-19 00:00:00

  • Augmenting weak semantic cognitive maps with an "abstractness" dimension.

    abstract::The emergent consensus on dimensional models of sentiment, appraisal, emotions, and values is on the semantics of the principal dimensions, typically interpreted as valence, arousal, and dominance. The notion of weak semantic maps was introduced recently as distribution of representations in abstract spaces that are n...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2013/308176

    authors: Samsonovich AV,Ascoli GA

    更新日期:2013-01-01 00:00:00

  • A Competitive Multiattribute Group Decision-Making Approach for the Game between Manufacturers.

    abstract::Under the competitive market environment, the game between manufacturers comes down to the competitive multiattribute group decision-making problem. In this study, the evaluation information of experts is given in the form of 2-dimension 2-tuple linguistic variables, and an approach is proposed for the competitive mul...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/8389035

    authors: Zhang Q,Jiang K,Yan M,Ma J

    更新日期:2019-11-11 00:00:00

  • Why people play: artificial lives acquiring play instinct to stabilize productivity.

    abstract::We propose a model to generate a group of artificial lives capable of coping with various environments which is equivalent to a set of requested task, and likely to show that the plays or hobbies are necessary for the group of individuals to maintain the coping capability with various changes of the environment as a w...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2012/197262

    authors: Tamura S,Inabayashi S,Hayakawa W,Yokouchi T,Mitsumoto H,Taketani H

    更新日期:2012-01-01 00:00:00

  • Single-Trial Evoked Potential Estimating Based on Sparse Coding under Impulsive Noise Environment.

    abstract::Estimating single-trial evoked potentials (EPs) corrupted by the spontaneous electroencephalogram (EEG) can be regarded as signal denoising problem. Sparse coding has significant success in signal denoising and EPs have been proven to have strong sparsity over an appropriate dictionary. In sparse coding, the noise gen...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/9672871

    authors: Yu N,Chen Y,Wu L,Lu H

    更新日期:2018-03-22 00:00:00

  • A red-light running prevention system based on artificial neural network and vehicle trajectory data.

    abstract::The high frequency of red-light running and complex driving behaviors at the yellow onset at intersections cannot be explained solely by the dilemma zone and vehicle kinematics. In this paper, the author presented a red-light running prevention system which was based on artificial neural networks (ANNs) to approximate...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2014/892132

    authors: Li P,Li Y,Guo X

    更新日期:2014-01-01 00:00:00

  • Classifying EEG Signals during Stereoscopic Visualization to Estimate Visual Comfort.

    abstract::With stereoscopic displays a sensation of depth that is too strong could impede visual comfort and may result in fatigue or pain. We used Electroencephalography (EEG) to develop a novel brain-computer interface that monitors users' states in order to reduce visual strain. We present the first system that discriminates...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2016/2758103

    authors: Frey J,Appriou A,Lotte F,Hachet M

    更新日期:2016-01-01 00:00:00

  • On Ev-Degree and Ve-Degree Topological Properties of Tickysim Spiking Neural Network.

    abstract::Topological indices are indispensable tools for analyzing networks to understand the underlying topology of these networks. Spiking neural network architecture (SpiNNaker or TSNN) is a million-core calculating engine which aims at simulating the behavior of aggregates of up to a billion neurons in real time. Tickysim ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/8429120

    authors: Cancan M

    更新日期:2019-06-02 00:00:00

  • A novel multiple instance learning method based on extreme learning machine.

    abstract::Since real-world data sets usually contain large instances, it is meaningful to develop efficient and effective multiple instance learning (MIL) algorithm. As a learning paradigm, MIL is different from traditional supervised learning that handles the classification of bags comprising unlabeled instances. In this paper...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/405890

    authors: Wang J,Cai L,Peng J,Jia Y

    更新日期:2015-01-01 00:00:00

  • SGB-ELM: An Advanced Stochastic Gradient Boosting-Based Ensemble Scheme for Extreme Learning Machine.

    abstract::A novel ensemble scheme for extreme learning machine (ELM), named Stochastic Gradient Boosting-based Extreme Learning Machine (SGB-ELM), is proposed in this paper. Instead of incorporating the stochastic gradient boosting method into ELM ensemble procedure primitively, SGB-ELM constructs a sequence of weak ELMs where ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/4058403

    authors: Guo H,Wang J,Ao W,He Y

    更新日期:2018-06-26 00:00:00

  • An Improved DSA-Based Approach for Multi-AUV Cooperative Search.

    abstract::Multi-AUV cooperative target search problem in unknown 3D underwater environment is not only a research hot spot but also a challenging task. To complete this task, each autonomous underwater vehicle (AUV) needs to move quickly without collision and cooperate with other AUVs to find the target. In this paper, an impro...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/2186574

    authors: Ni J,Yang L,Shi P,Luo C

    更新日期:2018-12-02 00:00:00

  • High-frequency electroencephalographic activity in left temporal area is associated with pleasant emotion induced by video clips.

    abstract::Recent findings suggest that specific neural correlates for the key elements of basic emotions do exist and can be identified by neuroimaging techniques. In this paper, electroencephalogram (EEG) is used to explore the markers for video-induced emotions. The problem is approached from a classifier perspective: the fea...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/762769

    authors: Kortelainen J,Väyrynen E,Seppänen T

    更新日期:2015-01-01 00:00:00

  • Comparison of classification methods for P300 brain-computer interface on disabled subjects.

    abstract::We report on tests with a mind typing paradigm based on a P300 brain-computer interface (BCI) on a group of amyotrophic lateral sclerosis (ALS), middle cerebral artery (MCA) stroke, and subarachnoid hemorrhage (SAH) patients, suffering from motor and speech disabilities. We investigate the achieved typing accuracy giv...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2011/519868

    authors: Manyakov NV,Chumerin N,Combaz A,Van Hulle MM

    更新日期:2011-01-01 00:00:00

  • Towards an Accessible Use of a Brain-Computer Interfaces-Based Home Care System through a Smartphone.

    abstract::This study proposes a home care system (HCS) based on a brain-computer interface (BCI) with a smartphone. The HCS provides daily help to motor-disabled people when a caregiver is not present. The aim of the study is two-fold: (1) to develop a BCI-based home care system to help end-users control their household applian...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2020/1843269

    authors: Sun KT,Hsieh KL,Syu SR

    更新日期:2020-08-28 00:00:00

  • Assessment of Multivariate Neural Time Series by Phase Synchrony Clustering in a Time-Frequency-Topography Representation.

    abstract::Most EEG phase synchrony measures are of bivariate nature. Those that are multivariate focus on producing global indices of the synchronization state of the system. Thus, better descriptions of spatial and temporal local interactions are still in demand. A framework for characterization of phase synchrony relationship...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/2406909

    authors: Porta-Garcia MA,Valdes-Cristerna R,Yanez-Suarez O

    更新日期:2018-03-21 00:00:00

  • An Improved Convolutional Neural Network Algorithm and Its Application in Multilabel Image Labeling.

    abstract::In today's society, image resources are everywhere, and the number of available images can be overwhelming. Determining how to rapidly and effectively query, retrieve, and organize image information has become a popular research topic, and automatic image annotation is the key to text-based image retrieval. If the sem...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/2060796

    authors: Cao J,Wu C,Chen L,Cui H,Feng G

    更新日期:2019-07-04 00:00:00

  • Improved Transductive Support Vector Machine for a Small Labelled Set in Motor Imagery-Based Brain-Computer Interface.

    abstract::Long and tedious calibration time hinders the development of motor imagery- (MI-) based brain-computer interface (BCI). To tackle this problem, we use a limited labelled set and a relatively large unlabelled set from the same subject for training based on the transductive support vector machine (TSVM) framework. We fi...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/2087132

    authors: Xu Y,Hua J,Zhang H,Hu R,Huang X,Liu J,Guo F

    更新日期:2019-11-25 00:00:00

  • Statistical modeling and analysis of laser-evoked potentials of electrocorticogram recordings from awake humans.

    abstract::This article is devoted to statistical modeling and analysis of electrocorticogram (ECoG) signals induced by painful cutaneous laser stimuli, which were recorded from implanted electrodes in awake humans. Specifically, with statistical tools of factor analysis and independent component analysis, the pain-induced laser...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2007/10479

    authors: Chen Z,Ohara S,Cao J,Vialatte F,Lenz FA,Cichocki A

    更新日期:2007-01-01 00:00:00

  • An effective hybrid cuckoo search algorithm with improved shuffled frog leaping algorithm for 0-1 knapsack problems.

    abstract::An effective hybrid cuckoo search algorithm (CS) with improved shuffled frog-leaping algorithm (ISFLA) is put forward for solving 0-1 knapsack problem. First of all, with the framework of SFLA, an improved frog-leap operator is designed with the effect of the global optimal information on the frog leaping and informat...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2014/857254

    authors: Feng Y,Wang GG,Feng Q,Zhao XJ

    更新日期:2014-01-01 00:00:00

  • The track of brain activity during the observation of TV commercials with the high-resolution EEG technology.

    abstract::We estimate cortical activity in normal subjects during the observation of TV commercials inserted within a movie by using high-resolution EEG techniques. The brain activity was evaluated in both time and frequency domains by solving the associate inverse problem of EEG with the use of realistic head models. In partic...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2009/652078

    authors: Astolfi L,Vecchiato G,De Vico Fallani F,Salinari S,Cincotti F,Aloise F,Mattia D,Marciani MG,Bianchi L,Soranzo R,Babiloni F

    更新日期:2009-01-01 00:00:00

  • Hybrid Degradation Equipment Remaining Useful Life Prediction Oriented Parallel Simulation considering Model Soft Switch.

    abstract::Equipment parallel simulation is an emerging simulation technology in recent years, and equipment remaining useful life (RUL) prediction oriented parallel simulation is an important branch of parallel simulation. An important concept in equipment parallel simulation is the model evolution driven by real-time data, inc...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/9179870

    authors: Ge C,Zhu Y,Di Y

    更新日期:2019-03-12 00:00:00

  • Music composition from the brain signal: representing the mental state by music.

    abstract::This paper proposes a method to translate human EEG into music, so as to represent mental state by music. The arousal levels of the brain mental state and music emotion are implicitly used as the bridge between the mind world and the music. The arousal level of the brain is based on the EEG features extracted mainly b...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2010/267671

    authors: Wu D,Li C,Yin Y,Zhou C,Yao D

    更新日期:2010-01-01 00:00:00

  • HDEC: A Heterogeneous Dynamic Ensemble Classifier for Binary Datasets.

    abstract::In recent years, ensemble classification methods have been widely investigated in both industry and literature in the field of machine learning and artificial intelligence. The main advantage of this approach is to benefit from a set of classifiers instead of using a single classifier with the aim of improving the pre...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2020/8826914

    authors: Ostvar N,Eftekhari Moghadam AM

    更新日期:2020-12-14 00:00:00

  • Prediction of Attendance Demand in European Football Games: Comparison of ANFIS, Fuzzy Logic, and ANN.

    abstract::An artificial neural network (ANN), adaptive neurofuzzy inference system (ANFIS) models, and fuzzy rule-based system (FRBS) models are developed to predict the attendance demand in European football games, in this paper. To determine the most successful method, each of the methods is analyzed under different situation...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/5714872

    authors: Şahin M,Erol R

    更新日期:2018-08-07 00:00:00

  • Chaos Quantum-Behaved Cat Swarm Optimization Algorithm and Its Application in the PV MPPT.

    abstract::Cat Swarm Optimization (CSO) algorithm was put forward in 2006. Despite a faster convergence speed compared with Particle Swarm Optimization (PSO) algorithm, the application of CSO is greatly limited by the drawback of "premature convergence," that is, the possibility of trapping in local optimum when dealing with non...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2017/1583847

    authors: Nie X,Wang W,Nie H

    更新日期:2017-01-01 00:00:00

  • Channel selection and feature projection for cognitive load estimation using ambulatory EEG.

    abstract::We present an ambulatory cognitive state classification system to assess the subject's mental load based on EEG measurements. The ambulatory cognitive state estimator is utilized in the context of a real-time augmented cognition (AugCog) system that aims to enhance the cognitive performance of a human user through com...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2007/74895

    authors: Lan T,Erdogmus D,Adami A,Mathan S,Pavel M

    更新日期:2007-01-01 00:00:00

  • A reinforcement learning framework for spiking networks with dynamic synapses.

    abstract::An integration of both the Hebbian-based and reinforcement learning (RL) rules is presented for dynamic synapses. The proposed framework permits the Hebbian rule to update the hidden synaptic model parameters regulating the synaptic response rather than the synaptic weights. This is performed using both the value and ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2011/869348

    authors: El-Laithy K,Bogdan M

    更新日期:2011-01-01 00:00:00

  • A Reweighted Scheme to Improve the Representation of the Neural Autoregressive Distribution Estimator.

    abstract::The neural autoregressive distribution estimator(NADE) is a competitive model for the task of density estimation in the field of machine learning. While NADE mainly focuses on the problem of estimating density, the ability for dealing with other tasks remains to be improved. In this paper, we introduce a simple and ef...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/6401645

    authors: Wang Z,Wu Q

    更新日期:2018-12-23 00:00:00