Скачать или смотреть Problem_13: Implement logistic regression using Scikit-learn

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Problem_12:
Implement logistic regression using Scikit-learn #pythoncode :

from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import accuracy_score

Load dataset
iris = load_iris()
X = iris.data
y = iris.target

Split dataset
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

Train logistic regression
model = LogisticRegression(max_iter=200)
model.fit(X_train, y_train)

Predict and evaluate
y_pred = model.predict(X_test)
accuracy = accuracy_score(y_test, y_pred)

print(f'Accuracy: {accuracy}')

#Sample_output

Accuracy: 1.0


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