Using AUC and accuracy in evaluating learning algorithms
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- The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy i…→Using AUC and accuracy in evaluating learning algorithmsLegacy edge — source detail unavailable
- A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Ba…→Using AUC and accuracy in evaluating learning algorithmsLegacy edge — source detail unavailable
- An insight into classification with imbalanced data: Empirical results and current trends…→Using AUC and accuracy in evaluating learning algorithmsLegacy edge — source detail unavailable
- Using AUC and accuracy in evaluating learning algorithms→Statistical Learning TheoryLegacy edge — source detail unavailable
- Using AUC and accuracy in evaluating learning algorithms→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
- Using AUC and accuracy in evaluating learning algorithms→A Tutorial on Support Vector Machines for Pattern RecognitionLegacy edge — source detail unavailable
- Using AUC and accuracy in evaluating learning algorithms→A training algorithm for optimal margin classifiersLegacy edge — source detail unavailable
- Using AUC and accuracy in evaluating learning algorithms→UCI Repository of machine learning databasesLegacy edge — source detail unavailable
- Using AUC and accuracy in evaluating learning algorithms→Signal detection theory and psychophysicsLegacy edge — source detail unavailable
- Using AUC and accuracy in evaluating learning algorithms→Text categorization with Support Vector Machines: Learning with many relevant featuresLegacy edge — source detail unavailable
- Using AUC and accuracy in evaluating learning algorithms→The use of the area under the ROC curve in the evaluation of machine learning algorithmsLegacy edge — source detail unavailable
- Using AUC and accuracy in evaluating learning algorithms→Basic principles of ROC analysisLegacy edge — source detail unavailable
- Using AUC and accuracy in evaluating learning algorithms→An Introduction to Support Vector MachinesLegacy edge — source detail unavailable
- Using AUC and accuracy in evaluating learning algorithms→Learning with KernelsLegacy edge — source detail unavailable
- Using AUC and accuracy in evaluating learning algorithms→A Simple Generalisation of the Area Under the ROC Curve for Multiple Class Classification…Legacy edge — source detail unavailable
- A Simple Generalisation of the Area Under the ROC Curve for Multiple Class Classification…→UCI Repository of machine learning databasesLegacy edge — source detail unavailable
- A Simple Generalisation of the Area Under the ROC Curve for Multiple Class Classification…→The use of the area under the ROC curve in the evaluation of machine learning algorithmsLegacy edge — source detail unavailable
- Basic principles of ROC analysis→Signal detection theory and psychophysicsLegacy edge — source detail unavailable
- A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Ba…→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
- A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Ba…→The use of the area under the ROC curve in the evaluation of machine learning algorithmsLegacy edge — source detail unavailable
- A Tutorial on Support Vector Machines for Pattern Recognition→A training algorithm for optimal margin classifiersLegacy edge — source detail unavailable
- A Tutorial on Support Vector Machines for Pattern Recognition→Statistical Learning TheoryLegacy edge — source detail unavailable
- Text categorization with Support Vector Machines: Learning with many relevant features→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
- The use of the area under the ROC curve in the evaluation of machine learning algorithms→Signal detection theory and psychophysicsLegacy edge — source detail unavailable
- The use of the area under the ROC curve in the evaluation of machine learning algorithms→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
- An insight into classification with imbalanced data: Empirical results and current trends…→A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Ba…Legacy edge — source detail unavailable
- An insight into classification with imbalanced data: Empirical results and current trends…→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
- An insight into classification with imbalanced data: Empirical results and current trends…→The use of the area under the ROC curve in the evaluation of machine learning algorithmsLegacy edge — source detail unavailable
- The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy i…→The use of the area under the ROC curve in the evaluation of machine learning algorithmsLegacy edge — source detail unavailable
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| Imbalanced Data Classification Techniques | Computer Science |
| Rough Sets and Fuzzy Logic | Computer Science |
| Advanced Statistical Process Monitoring | Decision Sciences |
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