from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
from joblib import dump

# Carregar e dividir o dataset
data = load_iris()
X = data.data
y = data.target
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

# Treinando o modelo
model = LogisticRegression()
model.fit(X_train, y_train)

# Salvar o modelo em um arquivo
model_filename = "model.pkl"
dump(model, model_filename)

print("Modelo treinado e salvo!")