query: How to approach logistic regression on skewed dataset
positive_passages.docid: 31300
positive_passages.text: Does an unbalanced sample matter when doing logistic regression?
negative_passages.docid: 131954
negative_passages.text: Choosing IRLS over gradient descent in logistic regression
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negative_passages.text: Measuring accuracy of a logistic regression-based model
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negative_passages.text: Bias the classification in logistic regression
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negative_passages.text: How to interpret coefficients from a logistic regression?
negative_passages.docid: 129169
negative_passages.text: Transforming positively skewed data with positive and negative values
negative_passages.docid: 49381
negative_passages.text: Simulation of logistic regression power analysis - designed experiments
negative_passages.docid: 15613
negative_passages.text: Interpretation of simple predictions to odds ratios in logistic regression
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negative_passages.text: Rare Events Logistic Regression
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negative_passages.text: How to simulate artificial data for logistic regression?
negative_passages.docid: 144448
negative_passages.text: Understanding lack of fit in logistic regression
negative_passages.docid: 76788
negative_passages.text: Interpreting logistic regression output in R
negative_passages.docid: 159012
negative_passages.text: Do I need a balanced sample (50% yes, 50% no) to run logistic regression?
negative_passages.docid: 42483
negative_passages.text: Logistic regression with {-1,+1} labels
negative_passages.docid: 95262
negative_passages.text: Can I still use logistic regression if some variables are not applied to all the observational units?
negative_passages.docid: 76276
negative_passages.text: Logistic Regression: Bernoulli vs. Binomial Response Variables
negative_passages.docid: 66215
negative_passages.text: Training a decision tree against unbalanced data