Pages that link to "Item:Q996413"

The following pages link to Cost-sensitive boosting for classification of imbalanced data (Q996413):

Displaying 50 items.

• Cost-sensitive boosting algorithms: do we really need them? (Q331693) (← links)
• A cost-sensitive ensemble method for class-imbalanced datasets (Q369767) (← links)
• A noise-detection based AdaBoost algorithm for mislabeled data (Q454443) (← links)
• Learning SVM with weighted maximum margin criterion for classification of imbalanced data (Q649635) (← links)
• A meta-heuristic approach for improving the accuracy in some classification algorithms (Q709124) (← links)
• Angle-based cost-sensitive multicategory classification (Q830425) (← links)
• Cost-sensitive ensemble learning: a unifying framework (Q832635) (← links)
• Integrated Fisher linear discriminants: an empirical study (Q898334) (← links)
• A review of boosting methods for imbalanced data classification (Q903116) (← links)
• Hierarchical fuzzy rule based classification systems with genetic rule selection for imbalanced data-sets (Q962879) (← links)
• An asymmetric classifier based on partial least squares (Q991957) (← links)
• Large margin cost-sensitive learning of conditional random fields (Q992002) (← links)
• Cost-sensitive boosting for classification of imbalanced data (Q996413) (← links)
• A closed-form reduction of multi-class cost-sensitive learning to weighted multi-class learning (Q1015231) (← links)
• RHSBoost: improving classification performance in imbalance data (Q1654228) (← links)
• Bounding the difference between RankRC and RankSVM and application to multi-level rare class kernel ranking (Q1741234) (← links)
• Imbalanced classification in sparse and large behaviour datasets (Q1741360) (← links)
• Calibrated asymmetric surrogate losses (Q1950846) (← links)
• Handling imbalance in hierarchical classification problems using local classifiers approaches (Q2036779) (← links)
• An overlap sensitive neural network for class imbalanced data (Q2036784) (← links)
• Constrained Naïve Bayes with application to unbalanced data classification (Q2103945) (← links)
• Enhancing techniques for learning decision trees from imbalanced data (Q2228292) (← links)
• Evaluation of the diagnostic power of thermography in breast cancer using Bayesian network classifiers (Q2262094) (← links)
• Progressive random \(k\)-labelsets for cost-sensitive multi-label classification (Q2398102) (← links)
• Training and assessing classification rules with imbalanced data (Q2435707) (← links)
• Imbalanced data classification using second-order cone programming support vector machines (Q2629845) (← links)
• Multi-class boosting with asymmetric binary weak-learners (Q2629847) (← links)
• Bootstrap FDA for counting positives accurately in imprecise environments (Q2643918) (← links)
• (Q2777427) (← links)
• Robust multiclass classification for learning from imbalanced biomedical data (Q2859924) (← links)
• Balanced gradient boosting from imbalanced data for clinical outcome prediction (Q2864066) (← links)
• Cost Sensitive SVM with Non-informative Examples Elimination for Imbalanced Postoperative Risk Management Problem (Q2950434) (← links)
• An improved boosting algorithm for small and imbalanced training sets (Q3014628) (← links)
• Stratified Normalization LogitBoost for Two-Class Unbalanced Data Classification (Q3102907) (← links)
• Grouped Variable Selection Using Area under the ROC with Imbalanced Data (Q3178533) (← links)
• FUSION OF EXTREME LEARNING MACHINE WITH FUZZY INTEGRAL (Q3195001) (← links)
• (Q3385416) (← links)
• An Improved Algorithm for SVMs Classification of Imbalanced Data Sets (Q3405715) (← links)
• Cost-Sensitive Learning of Fuzzy Rules for Imbalanced Classification Problems Using FURIA (Q3448611) (← links)
• (Q4406026) (← links)
• FEATURE SELECTION AND GRANULARITY LEARNING IN GENETIC FUZZY RULE-BASED CLASSIFICATION SYSTEMS FOR HIGHLY IMBALANCED DATA-SETS (Q4650061) (← links)
• Delta Boosting Machine with Application to General Insurance (Q4689973) (← links)
• OR Practice–Data Analytics for Optimal Detection of Metastatic Prostate Cancer (Q5003717) (← links)
• COST-SENSITIVE MULTI-CLASS ADABOOST FOR UNDERSTANDING DRIVING BEHAVIOR BASED ON TELEMATICS (Q5019037) (← links)
• Cost-sensitive incremental Classification under the MapReduce framework for Mining Imbalanced Massive Data Streams (Q5069698) (← links)
• Regularized receiver operating characteristic-based logistic regression for grouped variable selection with composite criterion (Q5220892) (← links)
• Logistic discrimination based on G-mean and F-measure for imbalanced problem (Q5275184) (← links)
• Structural, Syntactic, and Statistical Pattern Recognition (Q5466260) (← links)
• Application of credit‐scoring methods in a decision support system of investment for peer‐to‐peer lending (Q6056292) (← links)
• High dimensional binary classification under label shift: phase transition and regularization (Q6062484) (← links)