Data mining

This textbook gives an overview of statistical methods that have been developed during the last years due to increasing computer use, including random number generators, Monte Carlo methods, Markov Chain Monte Carlo (MCMC) methods, Bootstrap, EM algorithms, SIMEX, variable selection, density estimators, kernel estimators, orthogonal and local polynomial estimators, wavelet estimators, splines, and model assessment.

This textbook gives an overview of statistical methods that have been developed during the last years due to increasing computer use, including random number generators, Monte Carlo methods, Markov Chain Monte Carlo (MCMC) methods, Bootstrap, EM algorithms, SIMEX, variable selection, density estimators, kernel estimators, orthogonal and local polynomial estimators, wavelet estimators, splines, and model assessment.

Technological developments in recent years have been tremendous.

Technological developments in recent years have been tremendous.

Blockchain technologies, as an emerging distributed architecture and computing paradigm, have accelerated the development/application of the Cloud/GPU/Edge Computing, Artificial Intelligence, cyber physical systems, social networking, crowdsourcing and crowdsensing, 5G, trust management, and finance.

Smart Data: State-of-the-Art Perspectives in Computing and Applications explores smart data computing techniques to provide intelligent decision making and prediction services support for business, science, and engineering.

Smart Data: State-of-the-Art Perspectives in Computing and Applications explores smart data computing techniques to provide intelligent decision making and prediction services support for business, science, and engineering.

This book draws on author's wealth of knowledge working on numerous projects across many countries.

This book draws on author's wealth of knowledge working on numerous projects across many countries.

Scientists often collect samples of curves and other functional observations, and develop models where parameters are also functions.

Computational inference has taken its place alongside asymptotic inference and exact techniques in the standard collection of statistical methods.

Comparing Distributions refers to the statistical data analysis that encompasses the traditional goodness-of-fit testing.

This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework.

Many networked computer systems are far too vulnerable to cyber attacks that can inhibit their functioning, corrupt important data, or expose private information.

Data Mining in Agriculture represents a comprehensive effort to provide graduate students and researchers with an analytical text on data mining techniques applied to agriculture and environmental related fields.

The explosive growth of e-commerce and online environments has made the issue of information search and selection increasingly serious; users are overloaded by options to consider and they may not have the time or knowledge to personally evaluate these options.

In recent years there has been an explosion of network data - that is, measu- ments that are either of or from a system conceptualized as a network - from se- ingly all corners of science.

Data Mining for Business Applications presents the state-of-the-art research and development outcomes on methodologies, techniques, approaches and successful applications in the area.

Biometric  System and Data Analysis: Design, Evaluation, and Data Mining brings together aspects of statistics and machine learning to provide a comprehensive guide to evaluate, interpret and understand biometric data.

Every mathematical discipline goes through three periods of development: the naive, the formal, and the critical.

One of the "e;image"e; problems with wavelets is that because they have been a dominant area of interest (in nonparametric smoothing) people have forgotten that they are general tools with a fascinating role and future in other areas.

Remarkable advances in computation and data storage and the ready availability of huge data sets have been the keys to the growth of the new disciplines of data mining and machine learning, while the enormous success of the Human Genome Project has opened up the field of bioinformatics.

Social computing concerns the study of social behavior and context based on computational systems.

The use of geospatial technologies has become ubiquitous since the leading Internet vendors delivered a number of popular map websites.

This book brings together the latest research achievements from various areas of signal processing and related disciplines.

Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence, offering intuitive, efficient, and reliable methods for diagnosis, prediction, decision making, classification, troubleshooting, and data mining under uncertainty.

There can be no question, my dear Watson, of the value of exercise before breakfast.

This book provides balanced coverage of the existing results on sequence data mining as well as pattern types and associated pattern mining methods.

Data mining is the science and technology of exploring large and complex bodies of data in order to discover useful patterns.

Most commonly-used parametric and permutation statistical tests, such as the matched-pairs t test and analysis of variance, are based on non-metric squared distance functions that have very poor robustness characteristics.

The Akaike information criterion (AIC) derived as an estimator of the Kullback-Leibler information discrepancy provides a useful tool for evaluating statistical models, and numerous successful applications of the AIC have been reported in various fields of natural sciences, social sciences and engineering.

This book is about using interactive and dynamic plots on a computer screen as part of data exploration and modeling, both alone and as a partner with static graphics and non-graphical computational methods.

Advances in hardware technology have increased the capability to store and record personal data about consumers and individuals, causing concerns that personal data may be used for a variety of intrusive or malicious purposes.

The breakthrough idea of parallel coordinates has enchanted many people with its cleverness and power.

Data warehousing and data mining provide techniques for collecting information from distributed databases and for performing data analysis.

Data Streams: Models and Algorithms primarily discusses issues related to the mining aspects of data streams.

Methods of dimensionality reduction provide a way to understand and visualize the structure of complex data sets.

Graphics are great for exploring data, but how can they be used for looking at the large datasets that are commonplace to-day?

"e;If you torture the data long enough, Nature will confess,"e; said 1991 Nobel-winning economist Ronald Coase.

Data mining is a mature technology.

Data mining has emerged as a significant technology for gaining knowledge from vast quantities of data.

Data Mining and Knowledge Discovery Handbook organizes all major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository.

Knowledge, hidden in voluminous data repositories routinely created and maintained by today's applications, can be extracted by data mining.

In many applications, e.

While SAS and SPSS have many things in common, R is very different.

Conceptually, a database consists of objects and relationships.

Managing and Mining Uncertain Data, a survey with chapters by a variety of well known researchers in the data mining field, presents the most recent models, algorithms, and applications in the uncertain data mining field in a structured and concise way.

Information and communication technology and the Internet of Things play key roles in smart city projects.

Learn to develop blockchain-based distributed ledgers and deploy a Hyperledger Fabric network with concrete exercises and examplesKey FeaturesUpdated with the latest features and additions that come with Hyperledger Fabric 2Write your own smart contracts and services using Java and JavaScript on a Hyperledger Fabric networkDive into real-world blockchain challenges such as integration and scalabilityBook DescriptionBlockchain with Hyperledger Fabric - Second Edition is a refreshed and extended version of the successful book on practical Hyperledger Fabric blockchain development.

A comprehensive guide to building, managing, and securing scalable and reliable database and data warehousing applications using Postgres 12 and 13Key FeaturesSet up your database cluster and monitor, secure, and fine-tune it for optimal performanceLearn the fundamentals of database management and implement client- and server-side programming using SQL and PL/pgSQLExplore useful tips to develop efficient PostgreSQL database solutions from scratchBook DescriptionPostgreSQL is one of the fastest-growing open source object-relational database management systems (DBMS) in the world.