scientific article; zbMATH DE number 1753143
From MaRDI portal
Publication:4533353
zbMath0994.68128MaRDI QIDQ4533353
W. Philip Kegelmeyer, Nitesh V. Chawla, Lawrence O. Hall, Kevin W. Bowyer
Publication date: 10 June 2002
Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Related Items
An ensemble tree classifier for highly imbalanced data classification ⋮ Semi-supervised classification method through oversampling and common hidden space ⋮ Assessing the data complexity of imbalanced datasets ⋮ RSMOTE: a self-adaptive robust SMOTE for imbalanced problems with label noise ⋮ A hybrid data-level ensemble to enable learning from highly imbalanced dataset ⋮ Using the one-versus-rest strategy with samples balancing to improve pairwise coupling classification ⋮ Bayesian approach to discriminant problems for count data with application to multilocus short tandem repeat dataset ⋮ Cost-sensitive ensemble learning: a unifying framework ⋮ Matrix sketching for supervised classification with imbalanced classes ⋮ New hard-thresholding rules based on data splitting in high-dimensional imbalanced classification ⋮ Prediction of esophageal cancer using demographic, lifestyle, patient history, and basic clinical tests ⋮ Ordinal classification based on the sequential covering strategy ⋮ Classifying readmissions to a cardiac intensive care unit ⋮ Evaluating the importance of different communication types in romantic tie prediction on social media ⋮ Predicting social response to infectious disease outbreaks from Internet-based news streams ⋮ Manifold-based synthetic oversampling with manifold conformance estimation ⋮ Uncertainty-aware resampling method for imbalanced classification using evidence theory ⋮ Predicting hidden links in supply networks ⋮ Bayesian forecasting with a regime-switching zero-inflated multilevel Poisson regression model: an application to adolescent alcohol use with spatial covariates ⋮ The effect of imbalanced data sets on LDA: a theoretical and empirical analysis ⋮ Evaluation of neural networks and data mining methods on a credit assessment task for class imbalance problem ⋮ RHSBoost: improving classification performance in imbalance data ⋮ Gradient boosting for high-dimensional prediction of rare events ⋮ High dimensional classifiers in the imbalanced case ⋮ Techniques to improve ecological interpretability of black-box machine learning models. Case study on biological health of streams in the United States with gradient boosted trees ⋮ A novel, gradient boosting framework for sentiment analysis in languages where NLP resources are not plentiful: a case study for modern Greek ⋮ A structural SVM based approach for binary classification under class imbalance ⋮ Imbalanced learning for insurance using modified loss functions in tree-based models ⋮ Near-Bayesian support vector machines for imbalanced data classification with equal or unequal misclassification costs ⋮ A cost-sensitive ensemble method for class-imbalanced datasets ⋮ Post-boosting of classification boundary for imbalanced data using geometric mean ⋮ Optimizing predictive precision in imbalanced datasets for actionable revenue change prediction ⋮ Combining experts in order to identify binding sites in yeast and mouse genomic data ⋮ Probabilistic combination of classification rules and its application to medical diagnosis ⋮ Data science applications to string theory ⋮ Detecting and ordering salient regions ⋮ Hellinger distance decision trees are robust and skew-insensitive ⋮ Growing regression tree forests by classification for continuous object pose estimation ⋮ Learning a hybrid similarity measure for image retrieval ⋮ Improving SVM classification on imbalanced datasets by introducing a new bias ⋮ Large-scale distributed sparse class-imbalance learning ⋮ A review of boosting methods for imbalanced data classification ⋮ A robust correlation analysis framework for imbalanced and dichotomous data with uncertainty ⋮ Compressed labeling on distilled labelsets for multi-label learning ⋮ Using ensemble methods to deal with imbalanced data in predicting protein-protein interactions ⋮ Boosting imbalanced data learning with Wiener process oversampling ⋮ pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC ⋮ iPPI-PseAAC(CGR): identify protein-protein interactions by incorporating chaos game representation into PseAAC ⋮ MFSC: multi-voting based feature selection for classification of Golgi proteins by adopting the general form of Chou's PseAAC components ⋮ Learning SVM with weighted maximum margin criterion for classification of imbalanced data ⋮ Dynamic class imbalance learning for incremental LPSVM ⋮ Co-eye: a multi-resolution ensemble classifier for symbolically approximated time series ⋮ Tree-based space partition and merging ensemble learning framework for imbalanced problems ⋮ Enhancing techniques for learning decision trees from imbalanced data ⋮ Distance-based margin support vector machine for classification ⋮ Generative adversarial network based data augmentation to improve cervical cell classification model ⋮ iKernel: exact indexing for support vector machines ⋮ Bounding the difference between RankRC and RankSVM and application to multi-level rare class kernel ranking ⋮ Imbalanced classification in sparse and large behaviour datasets ⋮ How training on multiple time slices improves performance in churn prediction ⋮ Correlation for tree-shaped datasets and its Bayesian estimation ⋮ Trimmed LASSO regression estimator for binary response data ⋮ Cost-based feature selection for support vector machines: an application in credit scoring ⋮ Hierarchical fuzzy rule based classification systems with genetic rule selection for imbalanced data-sets ⋮ Optimizing airline passenger prescreening systems with Bayesian decision models ⋮ Fused variable screening for massive imbalanced data ⋮ An instance-based learning recommendation algorithm of imbalance handling methods ⋮ Customer base analysis: partial defection of behaviourally loyal clients in a non-contractual FMCG retail setting ⋮ Using pre \& post-processing methods to improve binding site predictions ⋮ Correcting classifiers for sample selection bias in two-phase case-control studies ⋮ An asymmetric classifier based on partial least squares ⋮ CCR: a combined cleaning and resampling algorithm for imbalanced data classification ⋮ Selective linearization for multi-block statistical learning ⋮ Option valuation under no-arbitrage constraints with neural networks ⋮ Ensembling classification models based on phalanxes of variables with applications in drug discovery ⋮ Cost-sensitive boosting for classification of imbalanced data ⋮ A novel SMOTE-based classification approach to online data imbalance problem ⋮ Handling imbalance in hierarchical classification problems using local classifiers approaches ⋮ An overlap sensitive neural network for class imbalanced data ⋮ An efficient weighted Lagrangian twin support vector machine for imbalanced data classification ⋮ Classification of signaling proteins based on molecular star graph descriptors using machine learning models ⋮ SVM classification for imbalanced data sets using a multiobjective optimization framework ⋮ LoRAS: an oversampling approach for imbalanced datasets ⋮ Optimised probabilistic active learning (OPAL) ⋮ RCSMOTE: range-controlled synthetic minority over-sampling technique for handling the class imbalance problem ⋮ RobROSE: a robust approach for dealing with imbalanced data in fraud detection ⋮ SMOTE ⋮ Chebyshev approaches for imbalanced data streams regression models ⋮ VFC-SMOTE: very fast continuous synthetic minority oversampling for evolving data streams ⋮ Density-based weighting for imbalanced regression ⋮ RB-CCR: radial-based combined cleaning and resampling algorithm for imbalanced data classification ⋮ RADE: resource-efficient supervised anomaly detection using decision tree-based ensemble methods ⋮ Cautious classification based on belief functions theory and imprecise relabelling ⋮ Modified neural network algorithms for predicting trading signals of stock market indices ⋮ Joint maximization of accuracy and information for learning the structure of a Bayesian network classifier ⋮ Fault diagnosis of gear rotor system based on collaborative filtering recommendation method ⋮ Predicting S-nitrosylation proteins and sites by fusing multiple features ⋮ Hybrid ResNet based on joint basic and attention modules for long-tailed classification ⋮ Prediction of brand stories spreading on social networks ⋮ Extending business failure prediction models with textual website content using deep learning ⋮ Difficulty factors and preprocessing in imbalanced data sets: an experimental study on artificial data ⋮ A Genetic Algorithm for Feature Selection and Granularity Learning in Fuzzy Rule-Based Classification Systems for Highly Imbalanced Data-Sets ⋮ Modeling surrender risk in life insurance: theoretical and experimental insight ⋮ Supervised Gene Function Prediction Using Spectral Clustering on Gene Co-expression Networks ⋮ Imbalanced data classification using second-order cone programming support vector machines ⋮ Protein subcellular localization in human and hamster cell lines: employing local ternary patterns of fluorescence microscopy images ⋮ Markov mean properties for cell death-related protein classification ⋮ A hierarchical multi-label classification algorithm for gene function prediction ⋮ Unnamed Item ⋮ Quantification of model risk that is caused by model misspecification ⋮ Adaptive kernel scaling support vector machine with application to a prostate cancer image study ⋮ Adaptive weighted over-sampling for imbalanced datasets based on density peaks clustering with heuristic filtering ⋮ Ensembles of cost-diverse Bayesian neural learners for imbalanced binary classification ⋮ Artificial intelligence in healthcare operations to enhance treatment outcomes: a framework to predict lung cancer prognosis ⋮ The detection and location estimation of disasters using Twitter and the identification of non-governmental organisations using crowdsourcing ⋮ Deep-learning-based partial pricing in a branch-and-price algorithm for personalized crew rostering ⋮ Feature extraction by statistical contact potentials and wavelet transform for predicting subcellular localizations in gram negative bacterial proteins ⋮ Cost Sensitive SVM with Non-informative Examples Elimination for Imbalanced Postoperative Risk Management Problem ⋮ A two-step anomaly detection based method for PU classification in imbalanced data sets ⋮ Integrating data augmentation and hybrid feature selection for small sample credit risk assessment with high dimensionality ⋮ A new instance density-based synthetic minority oversampling method for imbalanced classification problems ⋮ Imbalanced least squares regression with adaptive weight learning ⋮ Credit scoring with drift adaptation using local regions of competence ⋮ High dimensional binary classification under label shift: phase transition and regularization ⋮ A new non-kernel quadratic surface approach for imbalanced data classification in online credit scoring ⋮ Interpretable machine learning for imbalanced credit scoring datasets ⋮ Optimal task-driven time-dependent covariate-based maintenance policy ⋮ Classification Trees for Imbalanced Data: Surface-to-Volume Regularization ⋮ Robust cost-sensitive kernel method with Blinex loss and its applications in credit risk evaluation ⋮ Data adjusting strategy and optimized XGBoost algorithm for novel insider threat detection model ⋮ A novel oversampling technique for class-imbalanced learning based on SMOTE and natural neighbors ⋮ Missing data imputation in clinical trials using recurrent neural network facilitated by clustering and oversampling ⋮ Class imbalance learning using fuzzy ART and intuitionistic fuzzy twin support vector machines ⋮ Bayesian decision theory for tree-based adaptive screening tests with an application to youth delinquency ⋮ Bayesian analysis for imbalanced positive-unlabelled diagnosis codes in electronic health records ⋮ Financial futures prediction using fuzzy rough set and synthetic minority oversampling technique ⋮ A new classifier for imbalanced data based on a generalized density ratio model ⋮ Re-sampling of multi-class imbalanced data using belief function theory and ensemble learning ⋮ IMPACT OF DATA PREPROCESSING AND BALANCING ON DIABETES PREDICTION USING THE DECISION TREE TECHNIQUE ⋮ Three-way sampling for rapid attribute reduction ⋮ A random approximate reduct-based ensemble learning approach and its application in software defect prediction ⋮ An overlapping oriented imbalanced ensemble learning algorithm with weighted projection clustering grouping and consistent fuzzy sample transformation ⋮ AFNFS: adaptive fuzzy neighborhood-based feature selection with adaptive synthetic over-sampling for imbalanced data ⋮ FAC-fed: federated adaptation for fairness and concept drift aware stream classification ⋮ The role of mutual information in variational classifiers ⋮ Credit risk classification: an integrated predictive accuracy algorithm using artificial and deep neural networks ⋮ An Integrated machine learning and DEA-predefined performance outcome prediction framework with high-dimensional imbalanced data ⋮ Is this a violation? Learning and understanding norm violations in online communities ⋮ A new approach to generating virtual samples to enhance classification accuracy with small data -- a case of bladder cancer ⋮ Random forest based multiclass classification approach for highly skewed particle data ⋮ Imbalanced regression using regressor-classifier ensembles ⋮ Reconstructing production networks using machine learning ⋮ Sports analytics in the NFL: classifying the winner of the superbowl ⋮ Enhancing the predictive performance of ensemble models through novel multi-objective strategies: evidence from credit risk and business model innovation survey data ⋮ Frugal Gaussian clustering of huge imbalanced datasets through a bin-marginal approach ⋮ Automated imbalanced classification via layered learning ⋮ Prediction of postoperative recovery in patients with acoustic neuroma using machine learning and SMOTE-ENN techniques ⋮ Can generalised divergences help for invariant neural networks? ⋮ Hypergraph regularized semi-supervised support vector machine ⋮ Efficient change point detection and estimation in high-dimensional correlation matrices ⋮ Data augmentation using improved conditional GAN under extremely limited fault samples and its application in fault diagnosis of electric submersible pump ⋮ A SMOTE-based quadratic surface support vector machine for imbalanced classification with mislabeled information ⋮ Mixture copulas with discrete margins and their application to imbalanced data ⋮ Multiple kernel learning for label relation and class imbalance in multi-label learning ⋮ A Survey of Evolution in Predictive Models and Impacting Factors in Customer Churn ⋮ Training and assessing classification rules with imbalanced data ⋮ Unnamed Item ⋮ A comparative study of the use of large margin classifiers on seismic data ⋮ A vector-valued support vector machine model for multiclass problem ⋮ ADDRESSING IMBALANCED INSURANCE DATA THROUGH ZERO-INFLATED POISSON REGRESSION WITH BOOSTING ⋮ Minimax classifiers based on neural networks ⋮ The impact of preprocessing on data mining: an evaluation of classifier sensitivity in direct marketing ⋮ A multi-objective optimisation approach for class imbalance learning ⋮ A dynamic over-sampling procedure based on sensitivity for multi-class problems ⋮ Classification tree algorithm for grouped variables ⋮ Response transformation and profit decomposition for revenue uplift modeling ⋮ Densifying distance spaces for shape and image retrieval ⋮ Predictive models for bariatric surgery risks with imbalanced medical datasets ⋮ The Shape of Anisotropic Fractals: Scaling of Minkowski Functionals ⋮ An improved oversampling algorithm based on the samples' selection strategy for classifying imbalanced data ⋮ Coselection of features and instances for unsupervised rare category analysis ⋮ On handling negative transfer and imbalanced distributions in multiple source transfer learning ⋮ Regularized receiver operating characteristic-based logistic regression for grouped variable selection with composite criterion ⋮ AN ENSEMBLE TECHNIQUE FOR MULTI CLASS IMBALANCED PROBLEM USING PROBABILISTIC NEURAL NETWORKS ⋮ Learning algorithms to evaluate forensic glass evidence ⋮ An Improved Algorithm for SVMs Classification of Imbalanced Data Sets ⋮ A three-way decision ensemble method for imbalanced data oversampling ⋮ Massive datasets and machine learning for computational biomedicine: trends and challenges ⋮ OR Practice–Data Analytics for Optimal Detection of Metastatic Prostate Cancer ⋮ A Novel Approach to Feature Selection Based on Quality Estimation Metrics ⋮ COST-SENSITIVE MULTI-CLASS ADABOOST FOR UNDERSTANDING DRIVING BEHAVIOR BASED ON TELEMATICS ⋮ The effect of cognitive and behavioral factors on student success in a bottleneck business statistics course via deeper analytics ⋮ Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets ⋮ Replica analysis of overfitting in generalized linear regression models ⋮ Logistic discrimination based on G-mean and F-measure for imbalanced problem
Uses Software