How can I use Scikit-learn for machine learning in Python?

How can I use Scikit-learn for machine learning in Python?

Scikit-learn is a powerful library for machine learning in Python. You can start by installing it using pip: pip install scikit-learn. What specific task are you interested in, like classification or regression?

I'm interested in classification. Can you give me an example?

Sure! Here's a simple example using the Iris dataset. First, import the necessary libraries:

from sklearn import datasets
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestClassifier

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

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

# Create and train the model
model = RandomForestClassifier()
model.fit(X_train, y_train)

# Make predictions
predictions = model.predict(X_test)

What metrics can I use to evaluate the model's performance?

You can use several metrics such as accuracy, precision, recall, and F1-score. For example, you can use from sklearn.metrics import accuracy_score to calculate accuracy. Would you like to see how to implement that?