The following pages link to (Q4533353):
Displaying 50 items.
- A multi-objective optimisation approach for class imbalance learning (Q2275972) (← links)
- A dynamic over-sampling procedure based on sensitivity for multi-class problems (Q2275973) (← links)
- Classification tree algorithm for grouped variables (Q2282589) (← links)
- Response transformation and profit decomposition for revenue uplift modeling (Q2286984) (← links)
- Predictive models for bariatric surgery risks with imbalanced medical datasets (Q2288869) (← links)
- An improved oversampling algorithm based on the samples' selection strategy for classifying imbalanced data (Q2298314) (← links)
- Learning algorithms to evaluate forensic glass evidence (Q2318674) (← links)
- A three-way decision ensemble method for imbalanced data oversampling (Q2329593) (← links)
- Massive datasets and machine learning for computational biomedicine: trends and challenges (Q2329887) (← links)
- Difficulty factors and preprocessing in imbalanced data sets: an experimental study on artificial data (Q2360664) (← links)
- Feature extraction by statistical contact potentials and wavelet transform for predicting subcellular localizations in gram negative bacterial proteins (Q2413900) (← links)
- Training and assessing classification rules with imbalanced data (Q2435707) (← links)
- A vector-valued support vector machine model for multiclass problem (Q2446454) (← links)
- Minimax classifiers based on neural networks (Q2485035) (← links)
- The impact of preprocessing on data mining: an evaluation of classifier sensitivity in direct marketing (Q2497261) (← links)
- Densifying distance spaces for shape and image retrieval (Q2513322) (← links)
- Imbalanced data classification using second-order cone programming support vector machines (Q2629845) (← links)
- Protein subcellular localization in human and hamster cell lines: employing local ternary patterns of fluorescence microscopy images (Q2632347) (← links)
- Markov mean properties for cell death-related protein classification (Q2632745) (← links)
- A hierarchical multi-label classification algorithm for gene function prediction (Q2633227) (← links)
- Adaptive weighted over-sampling for imbalanced datasets based on density peaks clustering with heuristic filtering (Q2660951) (← links)
- Ensembles of cost-diverse Bayesian neural learners for imbalanced binary classification (Q2660967) (← links)
- Artificial intelligence in healthcare operations to enhance treatment outcomes: a framework to predict lung cancer prognosis (Q2669442) (← links)
- The detection and location estimation of disasters using Twitter and the identification of non-governmental organisations using crowdsourcing (Q2669448) (← links)
- Deep-learning-based partial pricing in a branch-and-price algorithm for personalized crew rostering (Q2669662) (← links)
- Integrating data augmentation and hybrid feature selection for small sample credit risk assessment with high dimensionality (Q2676331) (← links)
- Credit scoring with drift adaptation using local regions of competence (Q2677348) (← links)
- Financial futures prediction using fuzzy rough set and synthetic minority oversampling technique (Q2682606) (← links)
- A new approach to generating virtual samples to enhance classification accuracy with small data -- a case of bladder cancer (Q2686756) (← links)
- Prediction of postoperative recovery in patients with acoustic neuroma using machine learning and SMOTE-ENN techniques (Q2688778) (← links)
- A SMOTE-based quadratic surface support vector machine for imbalanced classification with mislabeled information (Q2691233) (← links)
- The Shape of Anisotropic Fractals: Scaling of Minkowski Functionals (Q2808812) (← links)
- Cost Sensitive SVM with Non-informative Examples Elimination for Imbalanced Postoperative Risk Management Problem (Q2950434) (← links)
- A Genetic Algorithm for Feature Selection and Granularity Learning in Fuzzy Rule-Based Classification Systems for Highly Imbalanced Data-Sets (Q3164067) (← links)
- (Q3385416) (← links)
- An Improved Algorithm for SVMs Classification of Imbalanced Data Sets (Q3405715) (← links)
- Coselection of features and instances for unsupervised rare category analysis (Q4969740) (← links)
- On handling negative transfer and imbalanced distributions in multiple source transfer learning (Q4969942) (← links)
- OR Practice–Data Analytics for Optimal Detection of Metastatic Prostate Cancer (Q5003717) (← links)
- A Novel Approach to Feature Selection Based on Quality Estimation Metrics (Q5016652) (← links)
- COST-SENSITIVE MULTI-CLASS ADABOOST FOR UNDERSTANDING DRIVING BEHAVIOR BASED ON TELEMATICS (Q5019037) (← links)
- Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets (Q5019887) (← links)
- Modeling surrender risk in life insurance: theoretical and experimental insight (Q5042783) (← links)
- Supervised Gene Function Prediction Using Spectral Clustering on Gene Co-expression Networks (Q5050390) (← links)
- Quantification of model risk that is caused by model misspecification (Q5073380) (← links)
- Adaptive kernel scaling support vector machine with application to a prostate cancer image study (Q5073413) (← links)
- A comparative study of the use of large margin classifiers on seismic data (Q5130137) (← links)
- ADDRESSING IMBALANCED INSURANCE DATA THROUGH ZERO-INFLATED POISSON REGRESSION WITH BOOSTING (Q5157763) (← links)
- (Q5211853) (← links)
- Regularized receiver operating characteristic-based logistic regression for grouped variable selection with composite criterion (Q5220892) (← links)
