query: Average Precision or FBeta & Decision Threshold Tuning for Binary Classifier
positive_passages.docid: 20531
positive_passages.text: Why is accuracy not the best measure for assessing classification models?
negative_passages.docid: 146981
negative_passages.text: Using Softmax activation function for multi-class classification
negative_passages.docid: 91880
negative_passages.text: Suggestions for cost-sensitive learning in a highly imbalanced setting
negative_passages.docid: 108282
negative_passages.text: How to choose between learning algorithms
negative_passages.docid: 86632
negative_passages.text: Only binary predictors -- ANOVA, regression, or other?
negative_passages.docid: 82239
negative_passages.text: Accuracy in neural network for regression
negative_passages.docid: 77590
negative_passages.text: Highly unbalanced test data set and balanced training data in classification
negative_passages.docid: 66215
negative_passages.text: Training a decision tree against unbalanced data
negative_passages.docid: 48226
negative_passages.text: How to adjust the hyperparameters of MLP classifier to get more perfect performance
negative_passages.docid: 117939
negative_passages.text: How to calculate the threshold value for numeric attributes in Quinlan's C4.5 algorithm?
negative_passages.docid: 118331
negative_passages.text: How to interpret margin of error in a non-binary poll?
negative_passages.docid: 91625
negative_passages.text: Classification/evaluation metrics for highly imbalanced data
negative_passages.docid: 63640
negative_passages.text: Logistic regression with categorical predictors
negative_passages.docid: 36100
negative_passages.text: 2-bit branch prediction accuracy
negative_passages.docid: 108205
negative_passages.text: Should I use a categorical cross-entropy or binary cross-entropy loss for binary predictions?
negative_passages.docid: 104621
negative_passages.text: On the hardness of data to learn
negative_passages.docid: 77815
negative_passages.text: Machine Learning with intended missing values