query: Class imbalance in data
positive_passages.docid: 31300
positive_passages.text: Does an unbalanced sample matter when doing logistic regression?
negative_passages.docid: 136012
negative_passages.text: why boosting method is sensitive to outliers
negative_passages.docid: 67557
negative_passages.text: Imputation of missing values for PCA
negative_passages.docid: 14138
negative_passages.text: Normality test with large data set
negative_passages.docid: 109407
negative_passages.text: ROC curve and confusion matrix in classifier performance evaluation
negative_passages.docid: 107608
negative_passages.text: Differentiation in support vector machine
negative_passages.docid: 81007
negative_passages.text: Help me understand Support Vector Machines
negative_passages.docid: 74123
negative_passages.text: Features for time series classification
negative_passages.docid: 64602
negative_passages.text: Logistic regression: class probabilities
negative_passages.docid: 117186
negative_passages.text: Algorithms for Time Series Anomaly Detection
negative_passages.docid: 145064
negative_passages.text: Techniques to detect overfitting
negative_passages.docid: 146981
negative_passages.text: Using Softmax activation function for multi-class classification
negative_passages.docid: 111170
negative_passages.text: Testing large dataset for normality - how and is it reliable?
negative_passages.docid: 142609
negative_passages.text: No regularisation term for bias unit in neural network
negative_passages.docid: 81918
negative_passages.text: Multicollinearity in Decision Tree
negative_passages.docid: 40442
negative_passages.text: Is up- or down-sampling imbalanced data actually that effective? Why?
negative_passages.docid: 91625
negative_passages.text: Classification/evaluation metrics for highly imbalanced data