Description
This advanced textbook provides social and behavioral science researchers with essential statistical machine learning methods for analyzing multivariate data. Written by leading experts in the field, it bridges traditional statistical approaches with modern machine learning techniques, making complex methodologies accessible to practitioners.
The book covers key topics including dimensionality reduction, clustering, classification, and latent variable models, with practical applications throughout the social sciences. Each chapter combines theoretical foundations with real-world examples, helping readers understand when and how to apply specific methods. The authors emphasize interpretability alongside predictive accuracy, ensuring results remain meaningful in social science contexts.
Ideal for graduate students, researchers, and practitioners, this Chapman & Hall publication equips you with the tools needed to extract meaningful insights from high-dimensional social science datasets and make data-driven decisions in your research.
Reviews
There are no reviews yet.