Questions tagged [oversampling]

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Explaining the logic behind the pipe_line method for cross-validation of imbalance datasets

Reading the following article: https://kiwidamien.github.io/how-to-do-cross-validation-when-upsampling-data.html There is an explanation of how to use ...
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oversampling multivariate time series data

For some classification needs. I have multivariate time series data composed from 4 stelite images in form of (145521 pixels, 4 dates, 2 bands) I made a classification with tempCNN to classify the ...
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Oversampling techniques for a class with 1 sample

I have 5 classes, one of them having only one sample. I've been researching techniques to oversample such as SMOTE and Bootstrapping but they do not work for the class with only one sample. I am ...
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57 views

How to increase the Accuracy after Oversampling?

The Accuracy before ovesampling : On Training : 98,54% On Testing : 98,21% The Accuracy <...
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84 views

How to use SMOTE to rebalance multiclass dataset when the target is one hot encoded with pd.get_dummies?

I'm using a multiclass dataset (cic-ids-2017), which is very imbalanced. I have already encoded the categorical feature (which is the target) using ...
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2answers
68 views

How to properly use oversampling without inflating results?

I am using with a tiny private dataset (over 192 samples) with 4 classes. A preprocessing step is trivial in order to do any classification. Among feature selection and extraction techniques, i ...
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2answers
390 views

Is it good practice to use SMOTE when you have a data set that has imbalanced classes when using BERT model for text classification?

I had a question related to SMOTE. If you have a data set that is imbalanced, is it correct to use SMOTE when you are using BERT? I believe I read somewhere that you do not need to do this since BERT ...
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50 views

How to apply variational autoencoder for oversampling with cross-validation?

Currently, I have an imbalanced data set with proportions 84% and 16%. I wanna use VAE as oversampling method and I want to determine the best proportions of data that results in better metrics. Also, ...