query: Accuracy in multi-label classification
positive_passages.docid: 20531
positive_passages.text: Why is accuracy not the best measure for assessing classification models?
negative_passages.docid: 43389
negative_passages.text: Multi-labeling with multiple colours in QGIS
negative_passages.docid: 30296
negative_passages.text: Rule-based labeling in QGIS
negative_passages.docid: 83655
negative_passages.text: Assumptions behind cross-validation
negative_passages.docid: 49594
negative_passages.text: Measuring accuracy of a logistic regression-based model
negative_passages.docid: 22203
negative_passages.text: Data normalization and standardization in neural networks
negative_passages.docid: 148032
negative_passages.text: Consistency strength of the "club ultrafilter"
negative_passages.docid: 77156
negative_passages.text: Intelligent point label placement in R
negative_passages.docid: 146981
negative_passages.text: Using Softmax activation function for multi-class classification
negative_passages.docid: 72166
negative_passages.text: Classification of Bayesian posterior probabilities
negative_passages.docid: 102744
negative_passages.text: Evaluating models by Loglogss, AUC, and Accuracy
negative_passages.docid: 94048
negative_passages.text: ROC vs Precision-recall curves on imbalanced dataset
negative_passages.docid: 145653
negative_passages.text: Balanced sampling for network training?
negative_passages.docid: 144805
negative_passages.text: Bag-of-Words for Text Classification: Why not just use word frequencies instead of TFIDF?
negative_passages.docid: 42256
negative_passages.text: Binary classification with strongly unbalanced classes
negative_passages.docid: 130691
negative_passages.text: Compare classifiers based on AUROC or accuracy?
negative_passages.docid: 79976
negative_passages.text: Feature Scaling and Mean Normalization