Instruct: Given a paper title, retrieve paper titles that are cited by the given paper.
Query: A systematic analysis of performance measures for classification tasks
A Review of Performance Evaluation Measures for Hierarchical Classifiers
A review of data complexity measures and their applicability to pattern classification problems
A comparative assessment of classification methods
Demographic Factors Improve Classification Performance
Optimizing F-Measures by Cost-Sensitive Classification
Similarity Measures for Categorical Data: A Comparative Evaluation
A framework for monitoring classifiers’ performance: when and why failure occurs?
Statistical Comparisons of Classifiers over Multiple Data Sets
Cost curves: An improved method for visualizing classifier performance
Dealing with the evaluation of supervised classification algorithms
Performance Analysis of Classification Algorithms on Medical Diagnoses-a Survey
Confidence Measures for Neural Network Classifiers
Predictive Accuracy : A Misleading Performance Measure for Highly Imbalanced Data
Micro and macro evaluation of classification rules
Properties and Benefits of Calibrated Classifiers
A Simple Generalisation of the Area Under the ROC Curve for Multiple Class Classification Problems
Diagnostic Accuracy Measures
Relating reinforcement learning performance to classification performance
A support vector method for multivariate performance measures
ROC Analysis of Classifiers in Machine Learning: A Survey
Beyond Accuracy, F-Score and ROC: A Family of Discriminant Measures for Performance Evaluation
2D/3D Pose Estimation and Action Recognition Using Multitask Deep Learning
Algorithm guided outlining of 105 pancreatic cancer liver metastases in Ultrasound
Rediscovering Workflow Models from Event-Based Data using Little Thumb
Predictors of lung function decline in scleroderma-related interstitial lung disease based on high-resolution computed tomography: implications for cohort enrichment in systemic sclerosis–associated interstitial lung disease trials