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Why these data are selected in data_process.py?
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**Contributors:** @jey-11 @Muthu2110 @vancheeswaran
**Scope / Problem Definition:**
- Dataset: https://www.kaggle.com/datasets/krishnaraj30/finance-loan-approval-prediction-data?select=train.cs…
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#### Learning Goals
Learn kNN algorithm for supervised classifications. Preferably use the kNN package from scikit-learn.
### Prerequisites
Some basic of kNN will be assumed. If scikit-learn is …
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**Is your feature request related to a problem? Please describe.**
A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
**Describe the solution you'd like**…
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There are several evaluation metrics that would be particularly beneficial for (binary) imbalanced classification problems and would be greatly appreciated additions. In terms of prioritizing implemen…
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There exists evidence that for classification problems with imbalanced datasets, subsampling of individuals where the number of samples in each class is the same, improves prediction:
[https://www.sc…
palVJ updated
4 years ago
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Current exclusive support of binary classification is limiting the use of the tool. Multi-class problems arise frequently and it would be nice to be able to use polyssifier for multiclass data.
- a …
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I am trying to build a model with multiple classification heads. MaskRCNN already has 3 heads - mask, box and class
How can we add another custom head such as another classification head. Is there a …
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Add data sampling to handle extremely large datasets.
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Hello Piotr !
Great library so far I've been enjoying trying out MLJAR, however I am wondering why are we using the threshold (binary classification case) leading to the highest accuracy to compute…