Questions tagged [imbalance]

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GridSearch on imbalanced datasets

Im trying to use gridsearch to find the best parameter for my model. Knowing that I have to implement nearmiss undersampling method while doing cross validation, should I fit my gridsearch on my ...
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13 views

Unseen samples(Rare category) during prediction?

Say if I train on these features(combination of categorical and numerical data), we could see that in feature x2, sample 4 has a rare entry 'b'. if during my train test split, I end up not getting ...
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0answers
33 views

Stratified K Fold Cross Validation in Orange: python script

I am using Orange to predict customer churn and compare different learners based on accuracy, F1, etc. As my problem is unbalanced (10% churn - 90% not churn), I want to oversample. However, when ...
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0answers
16 views

Unbalanced data set for multi-class classification algorithms

how can unbalanced data set for multi-class classification algorithms in python i am data set a contain three class . for example class1 , ...
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1answer
66 views

How and where to set weights in case of imbalanced cost sensitive learning in machine learning?

I confront with a binary classification machine learning task which is both slightly imbalanced and cost sensitive. I wonder what (and where in the modeling pipeline, say, in sklearn) is the best way ...
1
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2answers
385 views

Imbalanced Dataset (Transformers): How to Decide on Class Weights?

I'm using SimpleTranformers to train and evaluate a model. Since the dataset I am using is severely imbalanced, it is recommended that I assign weights to each ...
3
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1answer
43 views

Clustering with imbalanced data and groups

I have a problem that is about identifying clusters of highly correlated items. I initially focused on building a model and features that put similar data items close to each other. The main challenge ...
3
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1answer
2k views

unbalanced data classification

I used XGBoost to predict company's bankruptcy, which is an extremely unbalanced dataset. Although I tried weighting method as well as parameter tuning, the best result which I could obtain is as ...