Data Science with Matlab. Multivariate Methods

By G Peck

Large, high-dimensional data sets are common in the modern era of computer-based instrumentation and electronic data storage. High-dimensional data present many challenges for statistical visualization, analysis, and modeling. Data visualization, of course, is impossible beyond a few dimensions. As a result, pattern recognition, data preprocessing, and model selection must rely heavily on numerical methods. This book develops Multivariate Methods for work in Data Science. In addition, the book also develops examples and applications relating to such methods. The most important content in this book is the following: - "Introduction to Multivariate Methods" - "Multivariate Linear Regression" - "Estimation of Multivariate Regression Models" - "Set Up Multivariate Regression Problems" - "Multivariate General Linear Model" - "Fixed Effects Panel Model with Concurrent Correlation" - "Longitudinal Analysis" - "Multidimensional Scaling" - "Nonclassical and Nonmetric Multidimensional Scaling" - "Classical Multidimensional Scaling" - "Example: Multidimensional Scaling" - "Procrustes Analysis" - "Compare Handwritten Shapes Using Procrustes Analysis" - "Feature Selection" - "Select Subset of Features with Comparative Predictive Power" - "Feature Transformation" - "Nonnegative Matrix Factorization" - "Perform Nonnegative Matrix Factorization" - "Principal Component Analysis (PCA)" - "Analyze Quality of Life in U.S. Cities Using PCA" - "Factor Analysis" - "Analyze Stock Prices Using Factor Analysis" - "Robust Feature Selection Using NCA for Regression" - "Neighborhood Component Analysis (NCA) Feature Selection" - "t-SNE" - "t-SNE Output Function" - "Visualize High-Dimensional Data Using t-SNE" - "tsne Settings" - "Feature Extraction" - "Feature Extraction Workflow" - "Extract Mixed Signals"

• Format: Paperback
• Language: English
• ISBN: 1979500800
• ISBN13: 9781979500807
• Release Date: January 1
• Publisher: Createspace Independent Publishing Platform
• Length: 222 Pages
• Weight: 0.99 lbs.
• Dimensions: 0.5" x 8.0" x 10.0"