Classification Algorithms
Includes support-vector machines and random forests for supervised learning tasks.
Regression Algorithms
Offers logistic regression implemented via a LIBLINEAR wrapper.
Clustering Methods
Provides clustering algorithms such as k-means and DBSCAN for unsupervised learning.
Data Preprocessing and Model Evaluation
Includes utilities for preparing data and evaluating machine learning models.
Integration with Scientific Python Libraries
Works seamlessly with NumPy, SciPy, Pandas, Matplotlib, and Plotly.