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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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**Electricity Consumption**
https://nbviewer.jupyter.org/github/cs109-energy/cs109-energy.github.io/blob/master/iPython/Exploratory%20Analysis.ipynb
https://machinelearningmastery.com/how-to-load-an…
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While imbalanced-learn 0.X really focuses on samplers, over time we start to add additional methods like ensemble classifiers. We could think about releasing imbalanced-learn 1.X which could reorganiz…
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There are a couple of features/properties about **EPPI-reviewer** that I was unable to find in literature and/or documentation:
- [ ] I believe no **balancing method** is used since all machine l…
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Add [SMOTE|http://www.jair.org/papers/paper953.html], "Synthetic Minority Over-sampling Technique" for handling imbalanced datasets/ This is a more sophisticated means of balancing the dataset vs str…
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### Describe the issue linked to the documentation
Hi guys,
In the "ROC curve using micro-averaged OvR" part of the doc (https://scikit-learn.org/stable/auto_examples/model_selection/plot_roc.html#r…
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Hi, Thanks for the great work, I am really interested in this idea of using contrastive learning in imbalanced studies. I am just a bit confused about this `--balance` term in the argument, are you ju…
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According to the lecture, the steps usually are:
**Data preparation**
- Exploratory data analysis
- Detecting outliers
- Dealing with missing values
- Data discretization
- Imbalanced learning…
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### Problem: Rebalance with dask-cuda does not rebalance effectively
### Problem Context
We can not seem to rebalance with `dask-cuda` effectively which leads to imbalanced GPU usage.
This…