Implementação dos algoritmos de árvore de decisão ID3, C4.5 e CART do zero
Project description
Minhas Árvores
Implementação educacional dos algoritmos ID3, C4.5 e CART em Python.
Instalação
pip install numpy pandas scikit-learn
Uso
from minhas_arvores import ID3, C45, CART
import pandas as pd
dados = pd.DataFrame({
'Tempo': ['Sol', 'Nublado', 'Chuva'],
'Jogar': ['Não', 'Sim', 'Sim']
})
X = dados[['Tempo']]
y = dados['Jogar']
# Treinar
id3 = ID3()
id3.fit(X, y)
# Predizer
resultado = id3.predict({'Tempo': 'Sol'})
print(resultado)
Exemplo Completo
python exemplo_uso.py
Algoritmos
- ID3: Ganho de informação, categóricos apenas
- C4.5: Razão de ganho, suporta contínuos e missing values
- CART: Gini index, divisões binárias
Licença
MIT
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