Questions tagged [oversampling]
The oversampling tag has no usage guidance.
8
questions
0
votes
1answer
13 views
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 ...
1
vote
0answers
45 views
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 ...
0
votes
0answers
10 views
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 ...
0
votes
1answer
57 views
How to increase the Accuracy after Oversampling?
The Accuracy before ovesampling :
On Training : 98,54%
On Testing : 98,21%
The Accuracy <...
0
votes
0answers
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 ...
1
vote
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 ...
0
votes
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 ...
0
votes
0answers
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, ...
