About the Book
This book is designed to cover a number of topics in the data mining field. The techniques and algorithms presented are of practical utility, rather than selecting algorithms that perform well on small miniature data sets, the algorithms described in this book are geared for the discovery of patterns and knowledge hidden in large, real data sets. Algorithms presented in the book are illustrated in pseudocode. The pseudocode is similar to the “C” programming language.
This book gives full coverage of the related methods, from the classic topics of clustering and classification to database methods to more recent and advanced topics [e.g., Singular Valure Decomposition {SVD is a method of decomposing a matrix, usually called “A“, into three smaller matrices: “U“, “S“, and “V“. “U“ is an orthogonal matrix with unit vectors that are perpendicular to each other. It captures the direction of the data in A. “S“ is a diagonal matrix with values on the main diagonal only. It captures the magnitude or importance of the data in A, and the singular values are arranged in descending order. Lastly, “V“ is another orthogonal matrix that captures the correlation of the data in “A“}; Principal Component Analysis {a dimensionality reduction & machine learning method to simplify a large dataset into a smaller set while still maintaining significant patterns & trends}, Wavelets {tool that can reveal hidden information in signals}, Support Vector Machine {algorithm used for Classification & Regression problems}]. The exposition is accessible to beginners and advanced readers alike. The book gives the fundamental material first and the more advanced material in follow-up chapters.
About The Author
The author (Subir Chakrabarty) is having multi-disciplined qualifications in engineering, "operational research, management accountancy & financial management and a rich experience of 48 years in operations, plant revamping, project management, cost engineering, cost &financial management and application of statistical packages (SPSS & SAS). His achievements include teaching, training and grooming of 4,500 postgraduate "MBA" students.