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figs-compas-recidivism
imodels/figs-compas-recidivism
figs-compas-recidivism is a tabular classification model from imodels. Use it for the tabular classification task on the model card, and read the license before you ship it in a product. It is set up for sklearn. The card lists the license as mit.
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544
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Repo size
113 KB
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1
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Repo makeup
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.joblib113 KB · 97%
At a glance
- Task
- Tabular Classification
- Library
- sklearn
- License
- mit
- Access
- Public
- Created
- Aug 13, 2022
- Updated
- Aug 13, 2022
- SHA
- 3ce867c8
Datasets
Model card
From the Hugging Face model README
Load the data
from datasets import load_dataset
import imodels
import numpy as np
from sklearn.model_selection import GridSearchCV
import joblib
dataset = load_dataset("imodels/compas-recidivism")
df = pd.DataFrame(dataset['train'])
X_train = df.drop(columns=['is_recid'])
y_train = df['is_recid'].values
df_test = pd.DataFrame(dataset['test'])
X_test = df.drop(columns=['is_recid'])
y_test = df['is_recid'].values
Load the model
from huggingface_hub import hf_hub_url, cached_download
import joblib
import pandas as pd
REPO_ID = "imodels/figs-compas-recidivism"
FILENAME = "sklearn_model.joblib"
model = joblib.load(cached_download(
hf_hub_url(REPO_ID, FILENAME)
))
# model is a `imodels.FIGSClassifier`
Make prediction
preds = model.predict(X_test)
print('accuracy', np.mean(preds==y_test))
# accuracy 0.6759165485112416
- Task
- Tabular Classification
- Library
- sklearn
- License
- mit
- Created
- Aug 13, 2022
- Updated
- Aug 13, 2022