semvec/pypi-packages huggingface dataset:
BinaryClassificationMetrics 0.0.5
This package contains various binary classification metric methods.
License: MIT
Keywords: binary-classification,metrics

Binary Classification Metrics

This package contains various binary classification methods. The methods included are as follows:

1. Precision Score - precision_score(predicted,actual)
2. Recall Score - recall_score(predicted,actual)
3. Selectivity or True Negative Rate - true_negative_rate(predicted,actual)
4. Negative Predictive Value - negative_predictive_value(predicted,actual)
5. Miss Rate or False Negative Rate - miss_rate(predicted,actual)
6. Fall Out or False Positive Rate - fall_out_score(predicted,actual)
7. False Discovery Rate - false_discovery_rate(predicted,actual)
8. False Omission Rate - false_omission_rate(predicted,actual)
9. Weighted Average Precision Score - weighted_avg_precision_score(predicted,actual)
10. Weighted Average Recall Score - weighted_avg_recall_score(predicted,actual)
11. Confusion Matrix - confusion_matrix(predicted,actual) - Return False Pos,False Neg,True Pos,True Neg

* The two arguments are the predicted classes and actual classes of the classification.
* Higher Class Number equates to the positive label.
ravioliboosting 0.1.0
level tems
License: MIT
Requires Python: >=3.6

# ravioliboosting

levels tems

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install ravioliboosting.

```bash
pip install ravioliboosting
```

## Usage

ask me

## License
[MIT](https://choosealicense.com/licenses/mit/)