Scikit-learn: machine learning in Python
Scikit-learn is a popular machine learning library for Python that provides various tools for data analysis and modeling. It is built on top of NumPy, SciPy, and matplotlib and is used for tasks such as classification, regression, clustering, and dimensionality reduction. Installation Scikit-learn can be installed using pip: pip install scikit-learn Example: Classification with Support Vector Machines Here's an example of using Scikit-learn for classification with support vector machines (SVMs): from sklearn import datasets from sklearn.model_selection import train_test_split from sklearn.svm import SVC from sklearn.metrics import accuracy_score # Load the iris dataset iris = datasets.load_iris() # Split the dataset into training and testing sets X_train, X_test, y_train, y_test = train_test_split(iris.data, iris.target, test_size=0.2) # Create an SVM classifier with a linear kernel clf = SVC(kernel='linear') # Train the classifier on ...