query: Multiple class prediction with unbalanced data
positive_passages.docid: 23761
positive_passages.text: When is unbalanced data really a problem in Machine Learning?
negative_passages.docid: 147006
negative_passages.text: Consequences of unbalanced subgroups of categorical variables in logistic regression?
negative_passages.docid: 151342
negative_passages.text: Is there an optimal loss function for dealing with imbalanced classes?
negative_passages.docid: 37433
negative_passages.text: How to build a predictive model when more levels of a categorical predictor are possible than appear in the training data
negative_passages.docid: 63640
negative_passages.text: Logistic regression with categorical predictors
negative_passages.docid: 67179
negative_passages.text: AUC and class imbalance in training/test dataset
negative_passages.docid: 42624
negative_passages.text: Class imbalance strategies
negative_passages.docid: 98863
negative_passages.text: Which metric to use to evaluate highly imbalance classification model performance
negative_passages.docid: 12804
negative_passages.text: 10 class problems with 324 features - am I recognition class based on multiple features, class based on the pattern of one feature?
negative_passages.docid: 156500
negative_passages.text: SVM for unbalanced data
negative_passages.docid: 151799
negative_passages.text: Decision tree not using all features from training dataset
negative_passages.docid: 107366
negative_passages.text: How to set class weights for imbalanced classes in Keras?
negative_passages.docid: 69548
negative_passages.text: Simultaneously fitting multiple datasets
negative_passages.docid: 124976
negative_passages.text: How to do one-class text classification?
negative_passages.docid: 51420
negative_passages.text: Evaluating multiclass imbalanced problem per class
negative_passages.docid: 109407
negative_passages.text: ROC curve and confusion matrix in classifier performance evaluation
negative_passages.docid: 89791
negative_passages.text: Correlated features produce strange weights in Logistic Regression