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Model description

Hyperparameters

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Hyperparameter Value
bootstrap True
ccp_alpha 0.0
class_weight
criterion gini
max_depth
max_features sqrt
max_leaf_nodes
max_samples
min_impurity_decrease 0.0
min_samples_leaf 1
min_samples_split 2
min_weight_fraction_leaf 0.0
n_estimators 100
n_jobs
oob_score False
random_state
verbose 0
warm_start False

Model Plot

RandomForestClassifier()
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Evaluation Results

Metric Value
accuracy 0.9041
roc_auc 0.9157

How to Get Started with the Model

import joblib
from skops.hub_utils import download
download("sulpha/student_academic_success", "path_to_folder")
model = joblib.load(
    "model.pkl"
)

Model Card Authors

This model card is written by following authors:

@sulpha

Model Card Contact

You can contact the model card authors through following channels: github.com/sulphatet

Citation

Below you can find information related to citation.

BibTeX:

Valentim Realinho, Jorge Machado, Luís Baptista, & Mónica V. Martins. (2021). Predict students' dropout and academic success (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5777340

model_description

This is a RandomForest Classifier trained on student academic performance data.

limitations

This model is trained for educational purposes.

Confusion Matrix

Confusion Matrix

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