Keywords: مجموعه داده های نامتعادل; Ambient assisted living (AAL); Continuous remote monitoring; Context awareness; Internet of things (IoT); Machine learning; Imbalanced datasets; Big data; Cloud computing;
مقالات ISI مجموعه داده های نامتعادل (ترجمه نشده)
مقالات زیر هنوز به فارسی ترجمه نشده اند.
در صورتی که به ترجمه آماده هر یک از مقالات زیر نیاز داشته باشید، می توانید سفارش دهید تا مترجمان با تجربه این مجموعه در اسرع وقت آن را برای شما ترجمه نمایند.
در صورتی که به ترجمه آماده هر یک از مقالات زیر نیاز داشته باشید، می توانید سفارش دهید تا مترجمان با تجربه این مجموعه در اسرع وقت آن را برای شما ترجمه نمایند.
Keywords: مجموعه داده های نامتعادل; Multi-class classification; Imbalanced datasets; Multiple classifier system; Ensemble learning; Binary decomposition; Resampling techniques;
Keywords: مجموعه داده های نامتعادل; Topology preserving maps; Quality measures; SIM; MLHL-SIM; ViSOM; GNG; Beta distribution; Imbalanced datasets;
Keywords: مجموعه داده های نامتعادل; Aggregated conformal prediction; Imbalanced datasets; QSAR; Signature descriptors; Support vector machines;
Keywords: مجموعه داده های نامتعادل; Hesitant fuzzy sets; Feature selection; High dimensional datasets; Big data; Imbalanced datasets; Microarray datasets;
Keywords: مجموعه داده های نامتعادل; Imbalanced datasets; Tree-based ensembles; Ordering-based pruning; Bagging; Boosting
Keywords: مجموعه داده های نامتعادل; Improvement of computed regression predictions; Individual reliability estimates; Machine Learning; Pattern recognition; Imbalanced datasets; Artificial Neural Networks;
Keywords: مجموعه داده های نامتعادل; Imbalanced datasets; Overlapping; Feature weighting; Evolutionary fuzzy systems; Fuzzy rule based classification systems
Keywords: مجموعه داده های نامتعادل; Genetic and evolutionary fuzzy systems; Fuzzy rule-based classifiers; Imbalanced datasets
Keywords: مجموعه داده های نامتعادل; Fisher linear discriminants; Imbalanced datasets; Empirical thresholds; Neighborhood-preserving transformations; Iterative learning
DRCW-ASEG: One-versus-One distance-based relative competence weighting with adaptive synthetic example generation for multi-class imbalanced datasets
Keywords: مجموعه داده های نامتعادل; Multi-class problems; Imbalanced datasets; Ensemble learning; Binary decomposition; Synthetic samples generation;
Synergy of sampling techniques and ensemble classifiers for classification of urban environments using full-waveform LiDAR data
Keywords: مجموعه داده های نامتعادل; Full-waveform LiDAR; Imbalanced datasets; Data sampling; Ensemble classifiers; Machine learning;
CHI-BD: A fuzzy rule-based classification system for Big Data classification problems
Keywords: مجموعه داده های نامتعادل; Fuzzy Rule-Based Classification Systems; Big Data; Hadoop; MapReduce; Imbalanced datasets;
EMDID: Evolutionary multi-objective discretization for imbalanced datasets
Keywords: مجموعه داده های نامتعادل; Discretization; Imbalanced datasets; Evolutionary multi-objective optimization; Area under ROC curve;
Optimizing area under the ROC curve via extreme learning machines
Keywords: مجموعه داده های نامتعادل; Extreme learning machine (ELM); Area under the ROC curve (AUC); Imbalanced datasets; Multi-class AUC optimization;
Cost-sensitive linguistic fuzzy rule based classification systems under the MapReduce framework for imbalanced big data
Keywords: مجموعه داده های نامتعادل; Fuzzy rule based classification systems; Big data; MapReduce; Hadoop; Imbalanced datasets; Cost-sensitive learning
Boosting weighted ELM for imbalanced learning
Keywords: مجموعه داده های نامتعادل; Extreme learning machine; Weighted extreme learning machine; Imbalanced datasets; AdaBoost
Addressing imbalanced classification with instance generation techniques: IPADE-ID
Keywords: مجموعه داده های نامتعادل; Differential evolution; Instance generation; Nearest neighbor; Decision tree; Imbalanced datasets
A study of subgroup discovery approaches for defect prediction
Keywords: مجموعه داده های نامتعادل; Subgroup discovery; Rules; Defect prediction; Imbalanced datasets
Searching for rules to detect defective modules: A subgroup discovery approach
Keywords: مجموعه داده های نامتعادل; Defect prediction; Subgroup discovery; Imbalanced datasets; Rules
A two-stage evolutionary algorithm based on sensitivity and accuracy for multi-class problems
Keywords: مجموعه داده های نامتعادل; Classification; Multi-class; Sensitivity; Accuracy; Two-stage evolutionary algorithm; Imbalanced datasets
Analysis of preprocessing vs. cost-sensitive learning for imbalanced classification. Open problems on intrinsic data characteristics
Keywords: مجموعه داده های نامتعادل; Classification; Imbalanced datasets; Preprocessing; Cost-sensitive learning; Class overlap; Dataset shift
Determination of relative agrarian technical efficiency by a dynamic over-sampling procedure guided by minimum sensitivity
Keywords: مجموعه داده های نامتعادل; Neural networks; Multi-classification; Sensitivity; Accuracy; DEA-Montecarlo; Hybrid algorithm; Imbalanced datasets; Oversampling method; SMOTE; APS
Evolutionary q-Gaussian Radial Basis Function Neural Network to determine the microbial growth/no growth interface of Staphylococcus aureus
Keywords: مجموعه داده های نامتعادل; Imbalanced datasets; Synthetic Minority Over-Sampling Technique (SMOTE); q-Gaussian Radial Basis Function Neural Network; Predictive Microbiology; Memetic Algorithm
A dynamic over-sampling procedure based on sensitivity for multi-class problems
Keywords: مجموعه داده های نامتعادل; Classification; Multi-class; Sensitivity; Accuracy; Memetic algorithm; Imbalanced datasets; Over-sampling method; SMOTE
Development of a multi-classification neural network model to determine the microbial growth/no growth interface
Keywords: مجموعه داده های نامتعادل; Multi-Classification; Sensitivity; Growth/no growth interface; Accuracy; Memetic algorithm; Imbalanced datasets; Oversampling method; SMOTE; S. aureus