Hello HiClass

A minimalist example showing how to use HiClass to train and predict.

/home/docs/checkouts/readthedocs.org/user_builds/hiclass/envs/v5.0.1/lib/python3.12/site-packages/sklearn/base.py:474: FutureWarning: `BaseEstimator._validate_data` is deprecated in 1.6 and will be removed in 1.7. Use `sklearn.utils.validation.validate_data` instead. This function becomes public and is part of the scikit-learn developer API.
  warnings.warn(
[['Animal' 'Reptile' 'Lizard']
 ['Animal' 'Reptile' 'Snake']
 ['Animal' 'Mammal' 'Cow']
 ['Animal' 'Mammal' 'Sheep']]

from sklearn.ensemble import RandomForestClassifier

from hiclass import LocalClassifierPerNode

# Define data
X_train = [[1], [2], [3], [4]]
X_test = [[4], [3], [2], [1]]
Y_train = [
    ["Animal", "Mammal", "Sheep"],
    ["Animal", "Mammal", "Cow"],
    ["Animal", "Reptile", "Snake"],
    ["Animal", "Reptile", "Lizard"],
]

# Use random forest classifiers for every node
rf = RandomForestClassifier()
classifier = LocalClassifierPerNode(local_classifier=rf)

# Train local classifier per node
classifier.fit(X_train, Y_train)

# Predict
predictions = classifier.predict(X_test)
print(predictions)