Feature selection with neighborhood entropy-based cooperative game theory.

Abstract:

:Feature selection plays an important role in machine learning and data mining. In recent years, various feature measurements have been proposed to select significant features from high-dimensional datasets. However, most traditional feature selection methods will ignore some features which have strong classification ability as a group but are weak as individuals. To deal with this problem, we redefine the redundancy, interdependence, and independence of features by using neighborhood entropy. Then the neighborhood entropy-based feature contribution is proposed under the framework of cooperative game. The evaluative criteria of features can be formalized as the product of contribution and other classical feature measures. Finally, the proposed method is tested on several UCI datasets. The results show that neighborhood entropy-based cooperative game theory model (NECGT) yield better performance than classical ones.

journal_name

Comput Intell Neurosci

authors

Zeng K,She K,Niu X

doi

10.1155/2014/479289

subject

Has Abstract

pub_date

2014-01-01 00:00:00

pages

479289

eissn

1687-5265

issn

1687-5273

journal_volume

2014

pub_type

杂志文章
  • 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

  • Large-Truck Safety Warning System Based on Lightweight SSD Model.

    abstract::Transportation is an important link in the mining process, and large trucks are one of the important tools for mine transportation. Due to their large size and small driving position, large trucks have a blind spot, which is a hidden danger to the safe transportation of mines and has a great impact on production effic...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/2180294

    authors: Xiao D,Li H,Liu C,He Q

    更新日期:2019-10-13 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

  • Explore Interregional EEG Correlations Changed by Sport Training Using Feature Selection.

    abstract::This paper investigated the interregional correlation changed by sport training through electroencephalography (EEG) signals using the techniques of classification and feature selection. The EEG data are obtained from students with long-time professional sport training and normal students without sport training as bas...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2016/6184823

    authors: Gao J,Wang W,Zhang J

    更新日期:2016-01-01 00:00:00

  • Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer.

    abstract::Energy consumption forecasting (ECF) is an important policy issue in today's economies. An accurate ECF has great benefits for electric utilities and both negative and positive errors lead to increased operating costs. The paper proposes a semantic based genetic programming framework to address the ECF problem. In par...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/971908

    authors: Castelli M,Trujillo L,Vanneschi L

    更新日期:2015-01-01 00:00:00

  • Channel Projection-Based CCA Target Identification Method for an SSVEP-Based BCI System of Quadrotor Helicopter Control.

    abstract::The brain-computer interface (BCI) plays an important role in assisting patients with amyotrophic lateral sclerosis (ALS) to enable them to participate in communication and entertainment. In this study, a novel channel projection-based canonical correlation analysis (CP-CCA) target identification method for steady-sta...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/2361282

    authors: Gao Q,Zhang Y,Wang Z,Dong E,Song X,Song Y

    更新日期:2019-12-16 00:00:00

  • EEGLAB, SIFT, NFT, BCILAB, and ERICA: new tools for advanced EEG processing.

    abstract::We describe a set of complementary EEG data collection and processing tools recently developed at the Swartz Center for Computational Neuroscience (SCCN) that connect to and extend the EEGLAB software environment, a freely available and readily extensible processing environment running under Matlab. The new tools incl...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2011/130714

    authors: Delorme A,Mullen T,Kothe C,Akalin Acar Z,Bigdely-Shamlo N,Vankov A,Makeig S

    更新日期:2011-01-01 00:00:00

  • Retrieval of Semantic-Based Inspirational Sources for Emotional Design.

    abstract::In the conceptual design stage, inspirational sources play an important role in designers' creative thinking. This paper proposes a retrieval method for semantic-based inspirational sources, which helps designers obtain inspirational images in the conceptual design stage of emotional design. The core principle involve...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/4685187

    authors: Du J,Li Y,Ma J,Xiong Y,Li W

    更新日期:2018-11-08 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

  • Saliency Mapping Enhanced by Structure Tensor.

    abstract::We propose a novel efficient algorithm for computing visual saliency, which is based on the computation architecture of Itti model. As one of well-known bottom-up visual saliency models, Itti method evaluates three low-level features, color, intensity, and orientation, and then generates multiscale activation maps. Fi...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/875735

    authors: He Z,Chen X,Sun L

    更新日期:2015-01-01 00:00:00

  • Pilot Study on Gait Classification Using fNIRS Signals.

    abstract::Rehabilitation training is essential for motor dysfunction patients, and the training through their subjective motion intention, comparing to passive training, is more conducive to rehabilitation. This study proposes a method to identify motion intention of different walking states under the normal environment, by usi...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/7403471

    authors: Jin H,Li C,Xu J

    更新日期:2018-10-17 00:00:00

  • Estimation of critical gap based on Raff's definition.

    abstract::Critical gap is an important parameter used to calculate the capacity and delay of minor road in gap acceptance theory of unsignalized intersections. At an unsignalized intersection with two one-way traffic flows, it is assumed that two events are independent between vehicles' arrival of major stream and vehicles' arr...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2014/236072

    authors: Guo RJ,Wang XJ,Wang WX

    更新日期:2014-01-01 00:00:00

  • 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

  • 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

  • Temporal Association Rule Mining and Updating and Their Application to Blast Furnace in the Steel Industry.

    abstract::Blast furnace (BF) is the main method of modern iron-making. Ensuring the stability of the BF conditions can effectively improve the quality and output of iron and steel. However, operations of BF depend on mainly human experience, which causes two problems: (1) human experience is not objective and is difficult to in...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2020/7467213

    authors: Han Y,Yu D,Yin C,Zhao Q

    更新日期:2020-05-11 00:00:00

  • Construction Project Safety Performance Management Using Analytic Network Process (ANP) as a Multicriteria Decision-Making (MCDM) Tool.

    abstract::The paper addresses the context in which the construction industry is considered risky, as the intense labor and machine environment interacts with acceleration and overlapping activities. This situation results in accidents and fatalities. A high number of accidents and fatalities leads to additional costs and delays...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2020/2610306

    authors: Gunduz M,Khader BK

    更新日期:2020-02-25 00:00:00

  • An Approach to Improve SSD through Skip Connection of Multiscale Feature Maps.

    abstract::SSD (Single Shot MultiBox Detector) is one of the best object detection algorithms and is able to provide high accurate object detection performance in real time. However, SSD shows relatively poor performance on small object detection because its shallow prediction layer, which is responsible for detecting small obje...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2020/2936920

    authors: Zhang X,Gao Y,Ye F,Liu Q,Zhang K

    更新日期:2020-04-05 00:00:00

  • Application of Machine Learning in Postural Control Kinematics for the Diagnosis of Alzheimer's Disease.

    abstract::The use of wearable devices to study gait and postural control is a growing field on neurodegenerative disorders such as Alzheimer's disease (AD). In this paper, we investigate if machine-learning classifiers offer the discriminative power for the diagnosis of AD based on postural control kinematics. We compared Suppo...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2016/3891253

    authors: Costa L,Gago MF,Yelshyna D,Ferreira J,David Silva H,Rocha L,Sousa N,Bicho E

    更新日期:2016-01-01 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

  • Software Development Effort Estimation Using Regression Fuzzy Models.

    abstract::Software effort estimation plays a critical role in project management. Erroneous results may lead to overestimating or underestimating effort, which can have catastrophic consequences on project resources. Machine-learning techniques are increasingly popular in the field. Fuzzy logic models, in particular, are widely...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/8367214

    authors: Nassif AB,Azzeh M,Idri A,Abran A

    更新日期:2019-02-20 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

  • Developmental and Evolutionary Lexicon Acquisition in Cognitive Agents/Robots with Grounding Principle: A Short Review.

    abstract::Grounded language acquisition is an important issue, particularly to facilitate human-robot interactions in an intelligent and effective way. The evolutionary and developmental language acquisition are two innovative and important methodologies for the grounding of language in cognitive agents or robots, the aim of wh...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章,评审

    doi:10.1155/2016/8571265

    authors: Rasheed N,Amin SH

    更新日期:2016-01-01 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

  • Intelligence Is beyond Learning: A Context-Aware Artificial Intelligent System for Video Understanding.

    abstract::Understanding video files is a challenging task. While the current video understanding techniques rely on deep learning, the obtained results suffer from a lack of real trustful meaning. Deep learning recognizes patterns from big data, leading to deep feature abstraction, not deep understanding. Deep learning tries to...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2020/8813089

    authors: Ghozia A,Attiya G,Adly E,El-Fishawy N

    更新日期:2020-12-23 00:00:00

  • Evolutionary Spiking Neural Networks for Solving Supervised Classification Problems.

    abstract::This paper presents a grammatical evolution (GE)-based methodology to automatically design third generation artificial neural networks (ANNs), also known as spiking neural networks (SNNs), for solving supervised classification problems. The proposal performs the SNN design by exploring the search space of three-layere...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/4182639

    authors: López-Vázquez G,Ornelas-Rodriguez M,Espinal A,Soria-Alcaraz JA,Rojas-Domínguez A,Puga-Soberanes HJ,Carpio JM,Rostro-Gonzalez H

    更新日期:2019-03-28 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

  • Neural Basis of Intrinsic Motivation: Evidence from Event-Related Potentials.

    abstract::Human intrinsic motivation is of great importance in human behavior. However, although researchers have focused on this topic for decades, its neural basis was still unclear. The current study employed event-related potentials to investigate the neural disparity between an interesting stop-watch (SW) task and a boring...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/698725

    authors: Jin J,Yu L,Ma Q

    更新日期:2015-01-01 00:00:00

  • Modified Mahalanobis Taguchi System for Imbalance Data Classification.

    abstract::The Mahalanobis Taguchi System (MTS) is considered one of the most promising binary classification algorithms to handle imbalance data. Unfortunately, MTS lacks a method for determining an efficient threshold for the binary classification. In this paper, a nonlinear optimization model is formulated based on minimizing...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2017/5874896

    authors: El-Banna M

    更新日期:2017-01-01 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

  • A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method.

    abstract::Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheri...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2017/8734214

    authors: Yang JH,Cheng CH,Chan CP

    更新日期:2017-01-01 00:00:00