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| Adaptive | roc | -based ensembles of HMMs applied to anomaly detection |
| Application of Three-Class | roc | Analysis to Task-Based Image Quality Assessment of Simultaneous Dual-Isotope Myocardial Perfusion SPECT (MPS) |
| Approximating the multiclass | roc | by pairwise analysis |
| ARatio: Extending area under the | roc | curve for probabilistic labels |
| Area Under the | roc | Curve Maximization for Metric Learning |
| Assessing Classifiers from Two Independent Data Sets Using | roc | Analysis: A Nonparametric Approach |
| Boolean Combination of Classifiers in the | roc | Space |
| Building confidence regions for the | roc | surface |
| Case Study in the use of | roc | curves for Algorithm Design, A |
| Combining AHP and | roc | with GIS for Airport Site Selection: A Case Study in Libya |
| Comparison of non-parametric methods for assessing classifier performance in terms of | roc | parameters |
| Comparison of real and computer-simulated clustered mic | roc | alcifications on digital mammograms. ROC study |
| Constrained monotone regression of | roc | curves and histograms using splines and polynomials |
| Context, Computation, and Optimal | roc | Performance in Hierarchical Models |
| Deep | roc | Analysis and AUC as Balanced Average Accuracy, for Improved Classifier Selection, Audit and Explanation |
| Edge Detector Evaluation Using Empirical | roc | Curves |
| Efficient Multiclass | roc | Approximation by Decomposition via Confusion Matrix Perturbation Analysis |
| Efficient Pedestrian Detection by Directly Optimizing the Partial Area under the | roc | Curve |
| ensemble classifier learning approach to | roc | optimization, An |
| Estimating the | roc | Curve of Linearly Combined Dichotomizers |
| Estimating the uncertainty in the estimated mean area under the | roc | curve of a classifier |
| Exploration of Data Scene Characterization and 3D | roc | Evaluation for Hyperspectral Anomaly Detection |
| Generating | roc | curves for artificial neural networks |
| Hypervolume Under the | roc | Hypersurface of Near-Guessing and Near-Perfect Observers in N-Class Classification Tasks, The |
| Ideal Observers and Optimal | roc | Hypersurfaces in N-Class Classification |
| Identification of Mangrove Areas by Remote Sensing: The | roc | Curve Technique Applied to the Northwestern Mexico Coastal Zone Using Landsat Imagery |
| Introducing | roc | Curves as Error Measure Functions: A New Approach to Train ANN-Based Biomedical Data Classifiers |
| introduction to | roc | analysis, An |
| Iterative Boolean combination of classifiers in the | roc | space: An application to anomaly detection with HMMs |
| Kolmogorov-Smirnov and | roc | curve metrics for binary classification performance assessment are equivalent |
| Linear model combining by optimizing the Area under the | roc | curve |
| Maximizing area under | roc | curve for biometric scores fusion |
| Maximizing the area under the | roc | curve by pairwise feature combination |
| Meaning and Use of the Area under a Receiver Operating Characteristic ( | roc | ) Curve, The |
| Meaning and Use of the Volume Under a Three-Class | roc | Surface (VUS), The |
| Modeling Urban Dynamics Using Random Forest: Implementing | roc | And Toc For Model Evaluation |
| Multi-class | roc | analysis from a multi-objective optimisation perspective |
| Multiclass | roc | Front method for cost-sensitive classification, The |
| Null Distribution of Volume Under Ordered Three-Class | roc | Surface (VUS) With Continuous Measurements |
| Objective Assessment of Image Quality: III, | roc | Metrics, Ideal Observers, And Likelihood-Generating Functions |
| Objective evaluation of approaches of skin detection using | roc | analysis |
| On machine learning, | roc | analysis, and statistical tests of significance |
| On optimal reject rules and | roc | curves |
| On-road experimental study on driving anger identification model based on physiological features by | roc | curve analysis |
| Optimal Joint Detection and Estimation That Maximizes | roc | -Type Curves |
| Optimization of Restricted | roc | Surfaces in Three-Class Classification Tasks |
| Optimizing area under the | roc | curve using semi-supervised learning |
| Performance Analysis of Three-Class Classifiers: Properties of a 3-D | roc | Surface and the Normalized Volume Under the Surface for the Ideal Observer |
| Precision-recall operating characteristic (P- | roc | ) curves in imprecise environments |
| Relationship between identification metrics: Expected confusion and area under a | roc | curve |
| roc | Analysis and Cost-Sensitive Optimization for Hierarchical Classifiers |
| roc | analysis in ordinal regression learning |
| roc | analysis of ultrasound tissue characterization classifiers for breast cancer diagnosis |
| roc | curve analysis for validating objective image fusion metrics |
| roc | curve equivalence using the Kolmogorov-Smirnov test |
| roc | Curve Estimation and Hypothesis Testing: Applications to Breast Cancer Detection |
| roc | curve evaluation of edge detector performance |
| roc | curves and nonrandom data |
| roc | curves and video analysis optimization in intestinal capsule endoscopy |
| roc | Curves for Performance Evaluation of Video Sequences Processing Systems for Surveillance Applications |
| roc | curves for regression |
| roc | graphs with instance-varying costs |
| roc | manifold for classification systems, The |
| roc | Method for the Evaluation of Multi-class Segmentation/Classification Algorithms with Infrared Imagery |
| roc | representation for the discriminability of multi-classification markers |
| roc | skeleton for multiclass ROC estimation, The |
| roc | skeleton for multiclass ROC estimation, The |
| roc | -based cost-sensitive classification with a reject option |
| roc | -based reject rule for dichotomizers, A |
| Rule Extraction from Support Vector Machines: Measuring the Explanation Capability Using the Area under the | roc | Curve |
| Score Fusion by Maximizing the Area under the | roc | Curve |
| Selecting features in microarray classification using | roc | curves |
| Spatially Binned | roc | : A Comprehensive Saliency Metric |
| Special issue on | roc | Analysis in Pattern Recognition |
| Suite of Tools for | roc | Analysis of Spatial Models, A |
| Three-Class | roc | Analysis: A Decision Theoretic Approach Under the Ideal Observer Framework |
| Three-Class | roc | Analysis: The Equal Error Utility Assumption and the Optimality of Three-Class ROC Surface Using the Ideal Observer |
| Three-Class | roc | Analysis: The Equal Error Utility Assumption and the Optimality of Three-Class ROC Surface Using the Ideal Observer |
| Three-Class | roc | Analysis: Toward a General Decision Theoretic Solution |
| Understanding random guessing line in | roc | curve |
| Use of the Area Under the | roc | Curve in the Evaluation of Machine Learning Algorithms, The |
| Using theoretical | roc | curves for analysing machine learning binary classifiers |
| Validity of Three-Class Hotelling Trace (3-HT) in Describing Three-Class Task Performance: Comparison of Three-Class Volume Under | roc | Surface (VUS) and 3-HT, The |
| Variance estimation for two-class and multi-class | roc | analysis using operating point averaging |
| Yeast cell detection in color microscopic images using | roc | -optimized decoloring and segmentation |
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