Embedding Undersampling Rotation Forest for Imbalanced Problem.

Abstract:

:Rotation Forest is an ensemble learning approach achieving better performance comparing to Bagging and Boosting through building accurate and diverse classifiers using rotated feature space. However, like other conventional classifiers, Rotation Forest does not work well on the imbalanced data which are characterized as having much less examples of one class (minority class) than the other (majority class), and the cost of misclassifying minority class examples is often much more expensive than the contrary cases. This paper proposes a novel method called Embedding Undersampling Rotation Forest (EURF) to handle this problem (1) sampling subsets from the majority class and learning a projection matrix from each subset and (2) obtaining training sets by projecting re-undersampling subsets of the original data set to new spaces defined by the matrices and constructing an individual classifier from each training set. For the first method, undersampling is to force the rotation matrix to better capture the features of the minority class without harming the diversity between individual classifiers. With respect to the second method, the undersampling technique aims to improve the performance of individual classifiers on the minority class. The experimental results show that EURF achieves significantly better performance comparing to other state-of-the-art methods.

journal_name

Comput Intell Neurosci

authors

Guo H,Diao X,Liu H

doi

10.1155/2018/6798042

subject

Has Abstract

pub_date

2018-11-01 00:00:00

pages

6798042

eissn

1687-5265

issn

1687-5273

journal_volume

2018

pub_type

杂志文章
  • A novel design of 4-class BCI using two binary classifiers and parallel mental tasks.

    abstract::A novel 4-class single-trial brain computer interface (BCI) based on two (rather than four or more) binary linear discriminant analysis (LDA) classifiers is proposed, which is called a "parallel BCI." Unlike other BCIs where mental tasks are executed and classified in a serial way one after another, the parallel BCI u...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2008/437306

    authors: Geng T,Gan JQ,Dyson M,Tsui CS,Sepulveda F

    更新日期:2008-01-01 00:00:00

  • R2-Based Multi/Many-Objective Particle Swarm Optimization.

    abstract::We propose to couple the R2 performance measure and Particle Swarm Optimization in order to handle multi/many-objective problems. Our proposal shows that through a well-designed interaction process we could maintain the metaheuristic almost inalterable and through the R2 performance measure we did not use neither an e...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2016/1898527

    authors: Díaz-Manríquez A,Toscano G,Barron-Zambrano JH,Tello-Leal E

    更新日期:2016-01-01 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

  • String Grammar Unsupervised Possibilistic Fuzzy C-Medians for Gait Pattern Classification in Patients with Neurodegenerative Diseases.

    abstract::Neurodegenerative diseases that affect serious gait abnormalities include Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and Huntington disease (HD). These diseases lead to gait rhythm distortion that can be determined by stride time interval of footfall contact times. In this paper, we present a new m...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/1869565

    authors: Klomsae A,Auephanwiriyakul S,Theera-Umpon N

    更新日期:2018-06-13 00:00:00

  • 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 centro...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/109806

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

    更新日期:2015-01-01 00:00:00

  • A novel single neuron perceptron with universal approximation and XOR computation properties.

    abstract::We propose a biologically motivated brain-inspired single neuron perceptron (SNP) with universal approximation and XOR computation properties. This computational model extends the input pattern and is based on the excitatory and inhibitory learning rules inspired from neural connections in the human brain's nervous sy...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2014/746376

    authors: Lotfi E,Akbarzadeh-T MR

    更新日期:2014-01-01 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

  • 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

  • Neural-Based Compensation of Nonlinearities in an Airplane Longitudinal Model with Dynamic-Inversion Control.

    abstract::The inversion design approach is a very useful tool for the complex multiple-input-multiple-output nonlinear systems to implement the decoupling control goal, such as the airplane model and spacecraft model. In this work, the flight control law is proposed using the neural-based inversion design method associated with...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2017/8575703

    authors: Liu Y,Li Y,Jin F

    更新日期:2017-01-01 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

  • 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

  • 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

  • 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 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

  • Two Different Points of View through Artificial Intelligence and Vector Autoregressive Models for Ex Post and Ex Ante Forecasting.

    abstract::The ANN method has been applied by means of multilayered feedforward neural networks (MLFNs) by using different macroeconomic variables such as the exchange rate of USD/TRY, gold prices, and the Borsa Istanbul (BIST) 100 index based on monthly data over the period of January 2000 and September 2014 for Turkey. Vector ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/409361

    authors: Aydin AD,Caliskan Cavdar S

    更新日期:2015-01-01 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

  • 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

  • Ranking of Sites for Installation of Hydropower Plant Using MLP Neural Network Trained with GA: A MADM Approach.

    abstract::Every energy system which we consider is an entity by itself, defined by parameters which are interrelated according to some physical laws. In recent year tremendous importance is given in research on site selection in an imprecise environment. In this context, decision making for the suitable location of power plant ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2017/4152140

    authors: Shimray BA,Singh KM,Khelchandra T,Mehta RK

    更新日期:2017-01-01 00:00:00

  • Finger tapping clinimetric score prediction in Parkinson's disease using low-cost accelerometers.

    abstract::The motor clinical hallmarks of Parkinson's disease (PD) are usually quantified by physicians using validated clinimetric scales such as the Unified Parkinson's Disease Rating Scale (MDS-UPDRS). However, clinical ratings are prone to subjectivity and inter-rater variability. The PD medical community is therefore looki...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2013/717853

    authors: Stamatakis J,Ambroise J,Crémers J,Sharei H,Delvaux V,Macq B,Garraux G

    更新日期:2013-01-01 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

  • RnRTD: Intelligent Approach Based on the Relationship-Driven Neural Network and Restricted Tensor Decomposition for Multiple Accusation Judgment in Legal Cases.

    abstract::The use of intelligent judgment technology to assist in judgment is an inevitable trend in the development of judgment in contemporary social legal cases. Using big data and artificial intelligence technology to accurately determine multiple accusations involved in legal cases is an urgent problem to be solved in lega...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/6705405

    authors: Guo X,Zhang H,Ye L,Li S

    更新日期:2019-07-07 00:00:00

  • Predictive Modeling in Race Walking.

    abstract::This paper presents the use of linear and nonlinear multivariable models as tools to support training process of race walkers. These models are calculated using data collected from race walkers' training events and they are used to predict the result over a 3 km race based on training loads. The material consists of 1...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/735060

    authors: Wiktorowicz K,Przednowek K,Lassota L,Krzeszowski T

    更新日期:2015-01-01 00:00:00

  • n-Iterative Exponential Forgetting Factor for EEG Signals Parameter Estimation.

    abstract::Electroencephalograms (EEG) signals are of interest because of their relationship with physiological activities, allowing a description of motion, speaking, or thinking. Important research has been developed to take advantage of EEG using classification or predictor algorithms based on parameters that help to describe...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/4613740

    authors: Aguilar Cruz KA,Zagaceta Álvarez MT,Palma Orozco R,Medel Juárez JJ

    更新日期:2018-01-15 00:00:00

  • Annealing Ant Colony Optimization with Mutation Operator for Solving TSP.

    abstract::Ant Colony Optimization (ACO) has been successfully applied to solve a wide range of combinatorial optimization problems such as minimum spanning tree, traveling salesman problem, and quadratic assignment problem. Basic ACO has drawbacks of trapping into local minimum and low convergence rate. Simulated annealing (SA)...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2016/8932896

    authors: Mohsen AM

    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

  • Rifle Shooting Performance Correlates with Electroencephalogram Beta Rhythm Network Activity during Aiming.

    abstract::To study the relationship between brain network and shooting performance during shooting aiming, we collected electroencephalogram (EEG) signals from 40 skilled shooters during rifle shooting and calculated the EEG functional coupling, functional brain network topology, and correlation coefficients between these EEG c...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/4097561

    authors: Gong A,Liu J,Jiang C,Fu Y

    更新日期:2018-11-11 00:00:00

  • Reducing the Schizophrenia Stigma: A New Approach Based on Augmented Reality.

    abstract::Schizophrenia is a chronic mental disease that usually manifests psychotic symptoms and affects an individual's functionality. The stigma related to this disease is a serious obstacle for an adequate approach to its treatment. Stigma can, for example, delay the start of treatment, and it creates difficulties in interp...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2017/2721846

    authors: Silva RDC,Albuquerque SGC,Muniz AV,Filho PPR,Ribeiro S,Pinheiro PR,Albuquerque VHC

    更新日期:2017-01-01 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

  • 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

  • Cloud Model-Based Artificial Immune Network for Complex Optimization Problem.

    abstract::This paper proposes an artificial immune network based on cloud model (AINet-CM) for complex function optimization problems. Three key immune operators-cloning, mutation, and suppression-are redesigned with the help of the cloud model. To be specific, an increasing half cloud-based cloning operator is used to adjust t...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2017/5901258

    authors: Wang M,Feng S,Li J,Li Z,Xue Y,Guo D

    更新日期:2017-01-01 00:00:00