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Questions tagged [smote]

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0
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1answer
47 views

solving multi-class imbalance classification using smote and OSS

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 ...
1
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0answers
13 views

SMOTE caused my total nrows in train to fall to a very small proportion

I have a highly skewed dataset with minority class in target being just about 4%. I decided to apply SMOTE using library DMwR in R. Here is my target: ...
1
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0answers
9 views

SmoteBoost: Should SMOTE be ran individually for each iteration/tree in the boosting?

As per the paper on SmoteBoost, SMOTE is ran for each iteration of the boosting, generating N samples, which are further added to the original training data and the weight distribution of the ...
0
votes
1answer
15 views

Methods for augmenting binary datasets

I have a small (~100 samples) dataset with roughly 20 features which are mostly binary, and a few are numeric (~5). I wanted to use methods for augmenting the training set and see if I can get better ...
1
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0answers
56 views

Increase Specificity of a model using SMOTE arguments from DMwR package in R when training data is unbalanced

I'm working on a binary classification problem and training data which I'm using is unbalanced. I used SMOTE function from DMwR ...
0
votes
1answer
27 views

How to make multiple regression perform better for outliers? (without reducing effect of them)

I have a small dataset(about 60 samples) and I need it to predict well for high target values. There are only a few high values and all models I tried perform poorly for these high values. So I ...
1
vote
1answer
40 views

Optimizing decision threshold on model with oversampled/imbalanced data

I'm working on developing a model with a highly imbalanced dataset (0.7% Minority class). To remedy the imbalance, I was going to oversample using algorithms from imbalanced-learn library. I had a ...
0
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0answers
44 views

Are resampling techniques such as SMOTE and ADASYN really a good approach?

I get that resampling techniques are used when there is a class imbalance problem. But the techniques that i mention actually generate synthetic data from the real data. Since the generated data are ...
2
votes
0answers
48 views

A classification machine learning flow chart implimenting dimentionality reduction, upsampling, and cross validation [closed]

I would like to make a flow chart for an ML classifier and make sure that my thinking is correct. Here is a little about my sample: I have 3 classes and about 160 features. I suspect that some of ...
0
votes
1answer
190 views

Vertical and horizontal lines appearing on large confusion matrix?

I have produced a large heatmap-like confusion matrix and am seeing horizontal and vertical lines on it, so I'm trying to determine: What they mean Why they are there How I can improve on this ...
4
votes
1answer
413 views

How to avoid resampling part of pipeline on test data (imblearn package, SMOTE)

I am using the imblearn package to resample some data before applying other transformation/prediction techniques. Specfically, I am using SMOTE in a slightly unconventional way, as a data ...
2
votes
0answers
119 views

DBSMOTE on Short Text Classification

I am trying to use DBSMOTE(Density-Based Synthetic Oversampling TEqnique) to on a data set of short text--tweets to be specific. This will be used to train a classifier model in a multiclass ...
1
vote
1answer
395 views

Scripting code for class imbalance in Biolabs Orange

I'm trying to manipulate some data in Biolabs Orange, using the built in Python Script widget and information at Biolabs Orange tutorial on scripting. However, I'm struggling with taking the results ...
0
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0answers
71 views

Imbalanced data set: How to speed up synthetic minority oversampling technique, for highly dimensional data?

I am trying to over-sample/under-sample the minority/majority class respectively, for an imbalanced data set containing around 2 million rows with 40 columns, and would like to generate a balanced ...
7
votes
1answer
4k views

How do you apply SMOTE on text classification?

Synthetic Minority Oversampling Technique (SMOTE) is an oversampling technique used in an imbalanced dataset problem. So far I have an idea how to apply it on generic, structured data. But is it ...
1
vote
0answers
143 views

suggestion to implement undersample and oversample

My dataset has the following class distribution ...
1
vote
1answer
452 views

Logic behind SMOTE-NC?

In the SMOTE paper, the authors present the logic of creating synthetic examples when some of the features are nominal and some are continuous (section 6.1, SMOTE-NC). This example is provided: $...
0
votes
1answer
114 views

How to perform SMOTE-N when there is no majority vote?

In the SMOTE paper, the authors present the logic of creating synthetic examples when all features are nominal (section 6.2, SMOTE-N): To generate new minority class feature vectors, we can create ...
3
votes
2answers
12k views

SMOTE and multi class oversampling

I have read that the SMOTE package is implemented for binary classification. In the case of n classes, it creates additional examples for the smallest class. Can I balance all the classes by running ...
1
vote
0answers
272 views

Can SMOTE be applied over sequence of words (sentences)?

I have a highly unbalanced text classification data. I am trying to over-sample through SMOTE. I have a doubt that applying SMOTE over sequence of word indices will give me valid data points or not (...