query: Imbalanced dataset - Undersampling & multiple classifiers
positive_passages.docid: 17469
positive_passages.text: weighted cross entropy for imbalanced dataset - multiclass classification
negative_passages.docid: 129169
negative_passages.text: Transforming positively skewed data with positive and negative values
negative_passages.docid: 125509
negative_passages.text: Scikit Learn Missing Data - Categorical values
negative_passages.docid: 103779
negative_passages.text: Overfitting a logistic regression model
negative_passages.docid: 66215
negative_passages.text: Training a decision tree against unbalanced data
negative_passages.docid: 114711
negative_passages.text: Exact Sampling from Improper Mixtures
negative_passages.docid: 25745
negative_passages.text: How do you calculate precision and recall for multiclass classification using confusion matrix?
negative_passages.docid: 158440
negative_passages.text: Supervised learning with uncertain data?
negative_passages.docid: 67179
negative_passages.text: AUC and class imbalance in training/test dataset
negative_passages.docid: 51420
negative_passages.text: Evaluating multiclass imbalanced problem per class
negative_passages.docid: 156390
negative_passages.text: Gradient Boosting for Linear Regression - why does it not work?
negative_passages.docid: 3980
negative_passages.text: Reduce Classification Probability Threshold
negative_passages.docid: 135207
negative_passages.text: Repeated ANOVA unbalanced data
negative_passages.docid: 156676
negative_passages.text: How to compare features and classifiers which achieve perfect accuracy?
negative_passages.docid: 79498
negative_passages.text: Best methods to solve class imbalance problem and why?
negative_passages.docid: 113807
negative_passages.text: Testing Classification on Oversampled Imbalance Data
negative_passages.docid: 107720
negative_passages.text: Resampling / simulation methods: monte carlo, bootstrapping, jackknifing, cross-validation, randomization tests, and permutation tests