Data Mining and Decision Support - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data Mining and Decision Support write by Dunja Mladenic. This book was released on 2012-12-06. Data Mining and Decision Support available in PDF, EPUB and Kindle. Data mining deals with finding patterns in data that are by user-definition, interesting and valid. It is an interdisciplinary area involving databases, machine learning, pattern recognition, statistics, visualization and others. Decision support focuses on developing systems to help decision-makers solve problems. Decision support provides a selection of data analysis, simulation, visualization and modeling techniques, and software tools such as decision support systems, group decision support and mediation systems, expert systems, databases and data warehouses. Independently, data mining and decision support are well-developed research areas, but until now there has been no systematic attempt to integrate them. Data Mining and Decision Support: Integration and Collaboration, written by leading researchers in the field, presents a conceptual framework, plus the methods and tools for integrating the two disciplines and for applying this technology to business problems in a collaborative setting.
Decision Support Using Data Mining
Decision Support Using Data Mining - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Decision Support Using Data Mining write by Sarabjot S. Anand. This book was released on 1998. Decision Support Using Data Mining available in PDF, EPUB and Kindle. For senior managers, IT managers and data mining service providers, this text explains what data mining can do for an organization, providing guidelines on how to manage data mining projects.
Business Intelligence
Business Intelligence - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Business Intelligence write by Carlo Vercellis. This book was released on 2011-08-10. Business Intelligence available in PDF, EPUB and Kindle. Business intelligence is a broad category of applications and technologies for gathering, providing access to, and analyzing data for the purpose of helping enterprise users make better business decisions. The term implies having a comprehensive knowledge of all factors that affect a business, such as customers, competitors, business partners, economic environment, and internal operations, therefore enabling optimal decisions to be made. Business Intelligence provides readers with an introduction and practical guide to the mathematical models and analysis methodologies vital to business intelligence. This book: Combines detailed coverage with a practical guide to the mathematical models and analysis methodologies of business intelligence. Covers all the hot topics such as data warehousing, data mining and its applications, machine learning, classification, supply optimization models, decision support systems, and analytical methods for performance evaluation. Is made accessible to readers through the careful definition and introduction of each concept, followed by the extensive use of examples and numerous real-life case studies. Explains how to utilise mathematical models and analysis models to make effective and good quality business decisions. This book is aimed at postgraduate students following data analysis and data mining courses. Researchers looking for a systematic and broad coverage of topics in operations research and mathematical models for decision-making will find this an invaluable guide.
Data Mining and Statistics for Decision Making
Data Mining and Statistics for Decision Making - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data Mining and Statistics for Decision Making write by Stéphane Tufféry. This book was released on 2011-03-23. Data Mining and Statistics for Decision Making available in PDF, EPUB and Kindle. Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge. Data mining is usually associated with a business or an organization's need to identify trends and profiles, allowing, for example, retailers to discover patterns on which to base marketing objectives. This book looks at both classical and recent techniques of data mining, such as clustering, discriminant analysis, logistic regression, generalized linear models, regularized regression, PLS regression, decision trees, neural networks, support vector machines, Vapnik theory, naive Bayesian classifier, ensemble learning and detection of association rules. They are discussed along with illustrative examples throughout the book to explain the theory of these methods, as well as their strengths and limitations. Key Features: Presents a comprehensive introduction to all techniques used in data mining and statistical learning, from classical to latest techniques. Starts from basic principles up to advanced concepts. Includes many step-by-step examples with the main software (R, SAS, IBM SPSS) as well as a thorough discussion and comparison of those software. Gives practical tips for data mining implementation to solve real world problems. Looks at a range of tools and applications, such as association rules, web mining and text mining, with a special focus on credit scoring. Supported by an accompanying website hosting datasets and user analysis. Statisticians and business intelligence analysts, students as well as computer science, biology, marketing and financial risk professionals in both commercial and government organizations across all business and industry sectors will benefit from this book.
Data Mining Multi-Attribute Decision System. Facilitating Decision Support Through Data Mining Technique by Hierarchical Multi-Attribute Decision Models
Data Mining Multi-Attribute Decision System. Facilitating Decision Support Through Data Mining Technique by Hierarchical Multi-Attribute Decision Models - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data Mining Multi-Attribute Decision System. Facilitating Decision Support Through Data Mining Technique by Hierarchical Multi-Attribute Decision Models write by Pankaj Pathak. This book was released on 2020-11-09. Data Mining Multi-Attribute Decision System. Facilitating Decision Support Through Data Mining Technique by Hierarchical Multi-Attribute Decision Models available in PDF, EPUB and Kindle. Doctoral Thesis / Dissertation from the year 2020 in the subject Computer Science - Commercial Information Technology, Symbiosis International University, language: English, abstract: Data mining is coined one of the steps while discovering insights from large amounts of data which may be stored in databases, data warehouses, or in other information repositories. Data mining is now playing a significant role in seeking a decision support to draw higher profits by the modern business world. Various researchers studied the benefits of data mining processes and its adoption by business organizations, but very few of them have discussed the success factors of decision support projects. The Research Hypothesis states the involvement of the decision tree while adopting accuracy of classification and while emphasizing the impact factor or importance of the attributes rather than the information gain. The concept of involvement of impact factor rather than just accuracy can be utilized in developing the new algorithm whose performance improves over the existing algorithms. We proposed a new algorithm which improves accuracy and contributing effectively in decision tree learning. We presented an algorithm that resolves the above stated problem of confliction of class. We have introduced the impact factor and classified impact factor to resolve the conflict situation. We have used data mining technique in facilitating the decision support with improved performance over its existing companion. We have also addressed the unique problem which have not been addressed before. Definitely, the fusion of data mining and decision support can contribute to problem-solving by enabling the vast hidden knowledge from data and knowledge received from experts. We have discussed a lot of work done in the field of decision support and hierarchical multi-attribute decision models. Ample amount of algorithms are available which are used to classify the data in datasets. Most algorithms use the concept of information gain for classification purpose. Some Lacking areas also exist. There is a need for an ideal algorithm for large datasets. There is a need for handling the missing values. There is a need for removing attribute bias towards choosing a random class when a conflict occurs. There is a need for decision support model which takes the advantages of hierarchical multi-attribute classification algorithms.
