Metadata-Version: 2.1
Name: ingotdr
Version: 0.0.2
Summary: INGOT-DR (INterpretable GrOup Testing for Drug Resistance)
Home-page: https://github.com/hoomanzabeti/ingotdr
Author: Hooman Zabeti
Author-email: hzabeti@sfu.ca
License: UNKNOWN
Platform: UNKNOWN
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: pulp
Requires-Dist: sklearn

# INGOT-DR

**INGOT-DR** ( **IN**terpretable **G**r**O**up **T**esting for **D**rug **R**esistance) is an interpretable rule-based predictive model base on **Group Testing** and **Boolean Compressed Sesing**.

## Install
INGOT-DR can be installed from PyPI
```python
pip install ingotdr
```

## Train and evaluate an INGOT-DR classifier
```python
from sklearn.model_selection import train_test_split
from sklearn.metrics import balanced_accuracy_score
import pandas as pd
import ingot

X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=33, test_size=0.2, stratify=y)

clf = ingot.INGOTClassifier()
clf.fit(X_train,y_train)

y_pred = clf.predict(X_test)

print("Balanced accuracy: {}".format(balanced_accuracy_score(y_test, y_pred)))


```



