metadata

library_name: sklearn
tags:
  - sklearn
  - skops
  - tabular-classification
model_format: pickle
model_file: model.pkl
widget:
  structuredData:
    Age at enrollment:
      - 20
      - 19
      - 19
    Application mode:
      - 8
      - 6
      - 1
    Application order:
      - 5
      - 1
      - 5
    Course:
      - 2
      - 11
      - 5
    Curricular units 1st sem (approved):
      - 0
      - 6
      - 0
    Curricular units 1st sem (credited):
      - 0
      - 0
      - 0
    Curricular units 1st sem (enrolled):
      - 0
      - 6
      - 6
    Curricular units 1st sem (evaluations):
      - 0
      - 6
      - 0
    Curricular units 1st sem (grade):
      - 0
      - 14
      - 0
    Curricular units 1st sem (without evaluations):
      - 0
      - 0
      - 0
    Curricular units 2nd sem (approved):
      - 0
      - 6
      - 0
    Curricular units 2nd sem (credited):
      - 0
      - 0
      - 0
    Curricular units 2nd sem (enrolled):
      - 0
      - 6
      - 6
    Curricular units 2nd sem (evaluations):
      - 0
      - 6
      - 0
    Curricular units 2nd sem (grade):
      - 0
      - 13.666666666666666
      - 0
    Curricular units 2nd sem (without evaluations):
      - 0
      - 0
      - 0
    Daytime/evening attendance:
      - 1
      - 1
      - 1
    Debtor:
      - 0
      - 0
      - 0
    Displaced:
      - 1
      - 1
      - 1
    Educational special needs:
      - 0
      - 0
      - 0
    Father's occupation:
      - 10
      - 4
      - 10
    Father's qualification:
      - 10
      - 3
      - 27
    GDP:
      - 1.74
      - 0.79
      - 1.74
    Gender:
      - 1
      - 1
      - 1
    Inflation rate:
      - 1.4
      - -0.3
      - 1.4
    International:
      - 0
      - 0
      - 0
    Marital status:
      - 1
      - 1
      - 1
    Mother's occupation:
      - 6
      - 4
      - 10
    Mother's qualification:
      - 13
      - 1
      - 22
    Nacionality:
      - 1
      - 1
      - 1
    Previous qualification:
      - 1
      - 1
      - 1
    Scholarship holder:
      - 0
      - 0
      - 0
    Tuition fees up to date:
      - 1
      - 0
      - 0
    Unemployment rate:
      - 10.8
      - 13.9
      - 10.8
language:
  - en
pipeline_tag: tabular-classification

Model description

Hyperparameters

Click to expand

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

sulpha
/

student_academic_success