Questions tagged [imbalanced-datasets]

For questions that involve imbalanced (or unbalanced) datasets.

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How to deal with unbalanced data in multilabel classification problem

I have 3 possible solutions, but I am not sure if they are good. I think they are a bit clunky (especially 1st and 2nd). Use multiple small models. So instead of having the model that can tell you ...
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Evaluating a CNN -multi class model with two separate thresholds

I have a model that outputs three classes. But here instead of one threshold, it depends on a combination of two (user input threshold). One threshold varies from 0.1 to 1.0 and the other varies from ...
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Evaluating a convolutional neural network on an imbalanced (academic) dataset

I have trained a posture analysis network to classify in a video of humans recorded in public places if there is a) shake-hand between two humans, b) Standing close together that their hands touch ...
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Doesn't imbalanced data affect input variables too?

I was thinking today about how biased data affects machine learning performance, and I begin to wonder why class imbalance (or data imbalance in general) is only talked about in a classification ...
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30 views

Why am I not getting a good accuracy but bad precision and recall for this binary classification problem (with an unbalanced dataset)?

I'm working on a simple MLP classification problem where I need to have the output layer as softmax. The dataset that I've been using needs to pass through a parse that I made to remove NaN and change ...
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32 views

How to handle class imbalancing when the actual data are that way

My supervised learning training data are obtained from actual data; and in real cases, there's one class which happens less often than other classes, just around 5% of all cases. To be precise, the ...
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33 views

Handling imbalanced data with multiple targets

I have the model which has 3 outputs (it is a regression task, I have the angle of the steering wheel, brake and acceleration). I can divide my values to some smaller bins and in this way I can change ...
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1answer
34 views

Multi class text classification when having only one sample for classes

I have a dataset of texts, each text was identified with an ID number. I would like to do a prediction by finding the best match ID number for upcoming new texts. To use multi text classification, I ...
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32 views

Adding Class Weights for imbalanced dataset?

Suppose I have the following toy data set: Each instance has multiple labels at a time. Now you can see I have 2 instances for Label2, however, only one, one instance for other labels. It means, we ...
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75 views

How do I select the (number of) negative cases, if I'm given a set of positive cases?

We were given a list of labeled data (around 100) of known positive cases, i.e. people that have a certain disease, i.e. all these people are labeled with the same class (disease). We also have a much ...
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17 views

Is the PR AUC invariant under label flip?

The ROC-AUC curve is invariant under a flip of the labels. I don't know if it's a famous result, so I will give the proof below. My question is if the PR-AUC curve also has this property. I have not ...
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72 views

How robust are deep networks to class imbalance?

Before deep learning, I worked with machine learning problems where the data had a large class imbalance (30:1 or worse ratios). At that time, all the classifiers struggled, even after under-sampling ...
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34 views

Transforming neural network target values before training

Consider the scenario in which I am measuring certain $f(a,x)$, which i want to be the target value for some related input $g(a,x)$. In other words, I am trying to map $$g(a,x)\Rightarrow f(a,x)$$ I ...
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65 views

How to perform binary classification when one class is more predominant than the other?

Assuming we have big $m \times n$ input dataset, with $m \times 1$ output vector. It's a classification problem with only two possible values: either $1$ or $0$. Now, the problem is that almost all ...
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112 views

Is it possible to combine k-fold cross-validation and oversampling for a multi-class text classification task with imbalanced data?

I am dealing with an intent classification task on an Italian customer service data set. I've more or less 1.5k sentences and 29 classes (imbalanced). According to the literature, a good choice is to ...
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92 views

How can I use Generative Adversarial Networks to solve the imbalanced class problem?

Problem setting We have to do a binary classification of data given a training dataset $D$, where most items belong to class $A$ and some items belong to class $B$, so the classes are heavily ...