Rank: 1111 based on 113 downloads (last 30 days) and 3 files submitted
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Barnan Das

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Company/University
Washington State University

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Professional Interests:
Machine Learning, Data Mining, Data Science

 

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Files Posted by Barnan View all
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(last 30 days)
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07 Aug 2012 Performance Measures for Classification This function evaluates the common performance measures for classification models. Author: Barnan Das performance measures, classification, machine learning 40 0
  • 4.0
4.0 | 1 rating
07 Aug 2012 Screenshot RUSBoost RUSBoost is a boosting-based sampling algorithm that handles class imbalance in class labeled data. Author: Barnan Das class imbalance, machine learning, data mining 34 16
  • 5.0
5.0 | 5 ratings
26 Jun 2012 SMOTEBoost Implementation of SMOTEBoost algorithm used to handle class imbalance problem in data. Author: Barnan Das class imbalance, machine learning, data mining 39 2
  • 5.0
5.0 | 1 rating
Comments and Ratings by Barnan View all
Updated File Comments Rating
24 Feb 2013 RUSBoost RUSBoost is a boosting-based sampling algorithm that handles class imbalance in class labeled data. Author: Barnan Das

Alex, you need to set the Java CLASSPATH environment variable to the downloaded RUSBoost directory.

24 Feb 2013 RUSBoost RUSBoost is a boosting-based sampling algorithm that handles class imbalance in class labeled data. Author: Barnan Das

Lu Li, the last line of the code is correct. Although, the prediction in this case is '0', I have printed out the probability of the sample being '1' to indicate how poorly it is performing. A value of 1 - Prob(1) would give you the value of Prob(0). I hope it makes sense.

23 Feb 2013 RUSBoost RUSBoost is a boosting-based sampling algorithm that handles class imbalance in class labeled data. Author: Barnan Das

There is no automated way of generating ARFF file. Although, the WEKA GUI has one such option. If there are hundreds of features of the data, I think they should generated by a piece of code.

22 Feb 2013 RUSBoost RUSBoost is a boosting-based sampling algorithm that handles class imbalance in class labeled data. Author: Barnan Das

Please ensure that your data format complies with the ARFF standard. You can feed the appropriate ARFF format in "ARFFheader.txt" file. Please take a look at "README.txt" for more details on how to run a new dataset.

Comments and Ratings on Barnan's Files View all
Updated File Comment by Comments Rating
10 Aug 2014 RUSBoost RUSBoost is a boosting-based sampling algorithm that handles class imbalance in class labeled data. Author: Barnan Das Glampson, ben

HI When running on the file test.m I get the message that boosting is being aborted as "Too many iterations have loss > 0.5" is this expected after 3/4?

Also I wondered after training is there a way to re run the model on new data as it comes in?

Many thanks,

Ben

10 Aug 2014 SMOTEBoost Implementation of SMOTEBoost algorithm used to handle class imbalance problem in data. Author: Barnan Das Glampson, ben

Hi,

I'm really interested in using SMOTEboost for some research I'm working on. However, after running the file test.m I get the following error:

Error using SMOTEBoost (line 122)
Java exception occurred:
java.lang.IllegalArgumentException: Comparison method violates its general contract!

at java.util.TimSort.mergeLo(Unknown Source)

at java.util.TimSort.mergeAt(Unknown Source)

at java.util.TimSort.mergeCollapse(Unknown Source)

at java.util.TimSort.sort(Unknown Source)

at java.util.TimSort.sort(Unknown Source)

at java.util.Arrays.sort(Unknown Source)

at java.util.Collections.sort(Unknown Source)

at weka.filters.supervised.instance.SMOTE.doSMOTE(SMOTE.java:637)

at weka.filters.supervised.instance.SMOTE.batchFinished(SMOTE.java:489)

at weka.filters.Filter.useFilter(Filter.java:662)

Error in Test (line 34)
prediction = SMOTEBoost(train_data,test_data,'tree',false);

Any help would be most welcome.

Thanks

Ben

14 Jan 2014 Performance Measures for Classification This function evaluates the common performance measures for classification models. Author: Barnan Das eman, anum

21 May 2013 SMOTEBoost Implementation of SMOTEBoost algorithm used to handle class imbalance problem in data. Author: Barnan Das Kong, Alex

I have a question about this implementation: in every iteration, you don't generate new synthetic samples using SMOTE, and just re-assign the weights by averaging the positive instance set and negative instance set. Could you please explain why?
In the SMOTEBoost paper, the authors didn't say how to assign weights to those newly-generated samples, do you have any idea about this?

25 Feb 2013 RUSBoost RUSBoost is a boosting-based sampling algorithm that handles class imbalance in class labeled data. Author: Barnan Das li, lu

Sorry for being inquisitive, but I got another question: how updated weights ‘W’ are associated with resampled dataset 'RESAMPLED'? It seems in your code upadated weights are only associated with the original training data.

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