Questions tagged [imbalanced-datasets]
For questions that involve imbalanced (or unbalanced) datasets.
9
questions
0
votes
1answer
12 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 ...
0
votes
1answer
23 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 ...
0
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1answer
28 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 ...
3
votes
1answer
73 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 ...
2
votes
1answer
63 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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31 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 ...
2
votes
1answer
61 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 ...
4
votes
1answer
80 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 ...
