Computational business analytics. (2014)

• Record Type: Book
• Further Information: Note: By Subrata Das.
• Authors: Das, Subrata Kumar
• Contents: Analytics Background and Architectures; ANALYTICS DEFINED; ANALYTICS MODELING; ANALYTICS PROCESSES; ANALYTICS AND DATA FUSION Mathematical and Statistical Preliminaries; STATISTICS AND PROBABILITY THEORY; LINEAR ALGEBRA FUNDAMENTALS; MATHEMATICAL LOGIC; GRAPHS AND TREES; MEASURES OF PERFORMANCE; ALGORITHMIC COMPLEXITY Statistics for Descriptive Analytics; PROBABILITY DISTRIBUTIONS; DISCRETE PROBABILITY DISTRIBUTIONS; CONTINUOUS PROBABILITY DISTRIBUTIONS; GOODNESS-OF-FIT TEST Bayesian Probability and Inference; BAYESIAN INFERENCE; PRIOR PROBABILITIES Inferential Statistics and Predictive Analytics; CHISQUARE; TEST OF INDEPENDENCE; REGRESSION ANALYSES; BAYESIAN LINEAR REGRESSION; PRINCIPAL COMPONENT AND FACTOR ANALYSES; SURVIVAL ANALYSIS; AUTOREGRESSION MODELS Artificial Intelligence for Symbolic Analytics; ANALYTICS AND UNCERTAINTIES; NEO-LOGICIST APPROACH; NEO-PROBABILIST; NEO-CALCULIST APPROACH; NEO-GRANULARIST Probabilistic Graphical Modeling; NAIVE BAYESIAN CLASSIFIER (NBC); KDEPENDENCE NAIVE BAYESIAN CLASSIFIER (KNBC); BAYESIAN BELIEF NETWORKS Decision Support and Prescriptive Analytics; EXPECTED UTILITY THEORY AND DECISION TREES; INFLUENCE DIAGRAMS FOR DECISION SUPPORT; SYMBOLIC ARGUMENTATION FOR DECISION SUPPORT Time Series Modeling and Forecasting; PROBLEM MODELING; KALMAN FILTER (KF); MARKOV MODELS; DYNAMIC BAYESIAN NETWORKS (DBNS) Monte Carlo Simulation; MONTE CARLO APPROXIMATION; GIBBS SAMPLING; METROPOLIS-HASTINGS ALGORITHM; PARTICLE FILTER (PF) Cluster Analysis and Segmentation; HIERARCHICAL CLUSTERING; K-MEANS CLUSTERING; K-NEAREST NEIGHBORS; SUPPORT VECTOR MACHINES; NEURAL NETWORKS Machine Learning for Analytics Models; DECISION TREES; LEARNING NAIVE BAYESIAN CLASSIFIERS; LEARNING OF KNBC; BAYESIAN BELIEF NETWORKS; INDUCTIVE LOGIC PROGRAMMING Unstructured Data and Text Analytics; INFORMATION STRUCTURING AND EXTRACTION; BRIEF INTRODUCTION TO NLP; TEXT CLASSIFICATION AND TOPIC EXTRACTION Semantic Web; RESOURCE DESCRIPTION FRAMEWORK (RDF); DESCRIPTION LOGICS Analytics Tools; INTELLIGENT DECISION AIDING SYSTEM (IDAS); ENVIRONMENT FOR FIFTH GENERATION APPLICATIONS (E5); ANALYSIS OF TEXT (ATEXT); R AND MATLAB; SAS AND WEKA Analytics Case Studies ; RISK ASSESSMENT MODEL I3; RISK ASSESSMENT IN INDIVIDUAL LENDING USING IDAS; RISK ASSESSMENT IN COMMERCIAL LENDING USING E5 AND IDAS; FRAUD DETECTION; SENTIMENT ANALYSIS USING ATEXT Appendix A: Usage of Symbols; Appendix B: Examples and Sample Data; Appendix C: MATLAB and R Code Examples Index Further Reading appears at the end of each chapter.
• Edition: 1st
• Publisher Details: Boca Raton : Chapman & Hall/CRC
• Publication Date: 2014
• Extent: 1 online resource, illustrations
• Subjects: 658.40380285; Business intelligence -- Data processing; Strategic planning -- Data processing
• Languages: English
• ISBNs: 9781439890738
• Notes: Note: Description based on CIP data; resource not viewed.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.