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solving multi-class imbalance classification using smote and OSS

using “OneVsRestClassifier” from sklearn in Python to tune a customized binary classification into a multi-class classificationLogistic Regression as multiclass classification using PySpark and issuesImbalance classes problemSMOTE and multi class oversamplingWhich Classification Metrics Are Appropriate For Each Class Distribution Scenario?Evaluation methods for multi-class classificationIs it bad practice to use multi-class over multi-label classification?Which method should be considered to evaluate the imbalanced multi-class classification?Metrics to measure imbalanced multi-class problem

0

$begingroup$

I am trying to solve multi-class imbalance classification problem for that i am using SMOTE for oversampling and OSS for under-sampling. But I have a doubt as I am working on multi-class so i have to convert it into binary classification. So we can convert it using OVA/OAA. So how can I use OVA/OAA with both under-sampling and oversampling on the same data-set.

Please solve my problem, It will be a great help.

multiclass-classification smote

share|improve this question

asked Jan 28 at 14:34

Ayushi ChaplotAyushi Chaplot

1

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bumped to the homepage by Community♦ 3 mins ago

This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.

• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  Thank you so much for your response. Firstly I will use OVA for converting multiclass into binary like if I have 3 classes then I will make 1 class as positive and other two classes as negative so it will make 3 combinations then I will I apply Resampling on both negative and positive for all the three combination individually. After that I will train my classifier with resampled classes(positive+negative) of all the three combinations individually and then will combine the result of all the combinations. Is it the right way to do?
  $endgroup$
  – Ayushi Chaplot
  Jan 29 at 2:07
  

  
  
  
  

add a comment | 

0

$begingroup$

I am trying to solve multi-class imbalance classification problem for that i am using SMOTE for oversampling and OSS for under-sampling. But I have a doubt as I am working on multi-class so i have to convert it into binary classification. So we can convert it using OVA/OAA. So how can I use OVA/OAA with both under-sampling and oversampling on the same data-set.

Please solve my problem, It will be a great help.

multiclass-classification smote

share|improve this question

asked Jan 28 at 14:34

Ayushi ChaplotAyushi Chaplot

1

$endgroup$

bumped to the homepage by Community♦ 3 mins ago

This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.

• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  Thank you so much for your response. Firstly I will use OVA for converting multiclass into binary like if I have 3 classes then I will make 1 class as positive and other two classes as negative so it will make 3 combinations then I will I apply Resampling on both negative and positive for all the three combination individually. After that I will train my classifier with resampled classes(positive+negative) of all the three combinations individually and then will combine the result of all the combinations. Is it the right way to do?
  $endgroup$
  – Ayushi Chaplot
  Jan 29 at 2:07
  

  
  
  
  

add a comment | 

$begingroup$

I am trying to solve multi-class imbalance classification problem for that i am using SMOTE for oversampling and OSS for under-sampling. But I have a doubt as I am working on multi-class so i have to convert it into binary classification. So we can convert it using OVA/OAA. So how can I use OVA/OAA with both under-sampling and oversampling on the same data-set.

Please solve my problem, It will be a great help.

multiclass-classification smote

share|improve this question

asked Jan 28 at 14:34

Ayushi ChaplotAyushi Chaplot

1

$endgroup$

share|improve this question

asked Jan 28 at 14:34

Ayushi ChaplotAyushi Chaplot

1

share|improve this question

asked Jan 28 at 14:34

Ayushi ChaplotAyushi Chaplot

1

asked Jan 28 at 14:34

Ayushi ChaplotAyushi Chaplot

1

asked Jan 28 at 14:34

Ayushi ChaplotAyushi Chaplot

1

1 Answer
1

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oldest

votes

0

$begingroup$

If you convert your problem to a binary classification task, you do not need to worry about any conflict with re-sampling techniques. You can then just use the imblearn.combine which combines Oversampling and under-sampling in one algorithm. There are classes available for this but I have found SMOTEENN to produce better results. SMOTEENN

share|improve this answer

answered Jan 28 at 20:11

mbassmbass

262

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add a comment | 

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0

$begingroup$

If you convert your problem to a binary classification task, you do not need to worry about any conflict with re-sampling techniques. You can then just use the imblearn.combine which combines Oversampling and under-sampling in one algorithm. There are classes available for this but I have found SMOTEENN to produce better results. SMOTEENN

share|improve this answer

answered Jan 28 at 20:11

mbassmbass

262

$endgroup$

add a comment | 

0

$begingroup$

If you convert your problem to a binary classification task, you do not need to worry about any conflict with re-sampling techniques. You can then just use the imblearn.combine which combines Oversampling and under-sampling in one algorithm. There are classes available for this but I have found SMOTEENN to produce better results. SMOTEENN

share|improve this answer

answered Jan 28 at 20:11

mbassmbass

262

$endgroup$

add a comment | 

$begingroup$

If you convert your problem to a binary classification task, you do not need to worry about any conflict with re-sampling techniques. You can then just use the imblearn.combine which combines Oversampling and under-sampling in one algorithm. There are classes available for this but I have found SMOTEENN to produce better results. SMOTEENN

share|improve this answer

answered Jan 28 at 20:11

mbassmbass

262

$endgroup$

share|improve this answer

answered Jan 28 at 20:11

mbassmbass

262

answered Jan 28 at 20:11

mbassmbass

262

answered Jan 28 at 20:11

mbassmbass

262