New answers tagged unbalanced-classes
6
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class weighted classification
Against @gunes, I defend that you can use whatever metric you want. Yes accuracy may give you unexpected results in a imbalanced problem, but the choice of metric is based on the needs of your problem....
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5
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class weighted classification
If you want to include accuracy as a performance metric, balanced accuracy is a better choice than accuracy because of the imbalance in class distributions here. I would also recommend reading these ...
- 51.1k
1
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Accepted
What metrics work well in unbalanced assemblies?
The choice of metric depends on the needs of the application, not the problems with the methods/tools.
Accuracy is not a very bad metric; the main problem is that practitioners fail to use the ...
- 48.4k
0
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Do we need to split the data for Unsupervised Anomaly Detection?
The splitting of datasets is used to give an estimate of generalized performance, and is used for predictive models - models that are designed to take new datapoints and output new predictions for ...
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0
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References: t-test and Chi-squared test can be conducted with unequal sample sizes
Many intermediate-level applied statistical texts have the warnings mentioned in my comment. (One example, among many, is the text by Ott & Longnecker.)
Use Welch, not pooled t test. Here is an ...
- 49.7k
1
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How to correct Chi-square's p-value when working with very unbalanced contingency tables?
In addition to the other excellent answers:
To get more precise inference, you can model via logistic regression. That can always be done with a $2\times 2$ contingency table, and then use likelihood ...
- 64.8k
0
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How to correct Chi-square's p-value when working with very unbalanced contingency tables?
Imbalance alone is not an issue for a chi-squared test, although a small absolute number of counts can be - applying a chi-squared test to a 100:1 imbalanced dataset will work fine if you have a ...
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How to correct Chi-square's p-value when working with very unbalanced contingency tables?
The bottom line is that the proportions of diseased subjects among smokers and non-smokers are 0.0037 and 0.0011, respectively, and they are highly significantly different.
Because counts 16 and 20 ...
- 49.7k
1
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Dependent variable has no variance error in logit regression
The error message is clearly wrong: your data has a non-zero variance, though it is clearly imbalanced. What thus means for you? First, 115 positive samples are not much, if you can it might be wise ...
Tim♦
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