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A Practical Guide to Data Mining for Business and Industry.
Data mining is well on its way to becoming a recognized discipline in the overlapping areas of IT, statistics, machine learning, and AI. Practical Data Mining for Business presents a user-friendly approach to data mining methods, covering the typical uses to which it is applied. The methodology is c...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hoboken :
Wiley,
2014.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
| LEADER | 00000cam a2200000Mu 4500 | ||
|---|---|---|---|
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| 003 | OCoLC | ||
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| 006 | m o d | ||
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| 020 | |z 9781119977131 | ||
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| 050 | 4 | |a HF5415.125 .A42 2014 | |
| 082 | 0 | 4 | |a 006.312 |
| 049 | |a UAMI | ||
| 100 | 1 | |a Ahlemeyer-Stubbe, Andrea. | |
| 245 | 1 | 2 | |a A Practical Guide to Data Mining for Business and Industry. |
| 260 | |a Hoboken : |b Wiley, |c 2014. | ||
| 300 | |a 1 online resource (325 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a A Practical Guide to Data Mining for Business and Industry; Copyright; Contents; Glossary of terms; Part I Data Mining Concept; 1 Introduction; 1.1 Aims of the Book; 1.2 Data Mining Context; 1.2.1 Domain Knowledge; 1.2.2 Words to Remember; 1.2.3 Associated Concepts; 1.3 Global Appeal; 1.4 Example Datasets Used in This Book; 1.5 Recipe Structure; 1.6 Further Reading and Resources; 2 Data mining definition; 2.1 Types of Data Mining Questions; 2.1.1 Population and Sample; 2.1.2 Data Preparation; 2.1.3 Supervised and Unsupervised Methods; 2.1.4 Knowledge-Discovery Techniques. | |
| 505 | 8 | |a 2.2 Data Mining Process2.3 Business Task: Clarification of the Business Question behind the Problem; 2.4 Data: Provision and Processing of the Required Data; 2.4.1 Fixing the Analysis Period; 2.4.2 Basic Unit of Interest; 2.4.3 Target Variables; 2.4.4 Input Variables/Explanatory Variables; 2.5 Modelling: Analysis of the Data; 2.6 Evaluation and Validation during the Analysis Stage; 2.7 Application of Data Mining Results and Learning from the Experience; Part II Data Mining Practicalities; 3 All about data; 3.1 Some Basics; 3.1.1 Data, Information, Knowledge and Wisdom. | |
| 505 | 8 | |a 3.1.2 Sources and Quality of Data3.1.3 Measurement Level and Types of Data; 3.1.4 Measures of Magnitude and Dispersion; 3.1.5 Data Distributions; 3.2 Data Partition: Random Samples for Training, Testing and Validation; 3.3 Types of Business Information Systems; 3.3.1 Operational Systems Supporting Business Processes; 3.3.2 Analysis-Based Information Systems; 3.3.3 Importance of Information; 3.4 Data Warehouses; 3.4.1 Topic Orientation; 3.4.2 Logical Integration and Homogenisation; 3.4.3 Reference Period; 3.4.4 Low Volatility; 3.4.5 Using the Data Warehouse. | |
| 505 | 8 | |a 3.5 Three Components of a Data Warehouse: DBMS, DB and DBCS3.5.1 Database Management System (DBMS); 3.5.2 Database (DB); 3.5.3 Database Communication Systems (DBCS); 3.6 Data Marts; 3.6.1 Regularly Filled Data Marts; 3.6.2 Comparison between Data Marts and Data Warehouses; 3.7 A Typical Example from the Online Marketing Area; 3.8 Unique Data Marts; 3.8.1 Permanent Data Marts; 3.8.2 Data Marts Resulting from Complex Analysis; 3.9 Data Mart: Do's and Don'ts; 3.9.1 Do's and Don'ts for Processes; 3.9.2 Do's and Don'ts for Handling; 3.9.3 Do's and Don'ts for Coding/Programming; 4 Data Preparation. | |
| 505 | 8 | |a 4.1 Necessity of Data Preparation4.2 From Small and Long to Short and Wide; 4.3 Transformation of Variables; 4.4 Missing Data and Imputation Strategies; 4.5 Outliers; 4.6 Dealing with the Vagaries of Data; 4.6.1 Distributions; 4.6.2 Tests for Normality; 4.6.3 Data with Totally Different Scales; 4.7 Adjusting the Data Distributions; 4.7.1 Standardisation and Normalisation; 4.7.2 Ranking; 4.7.3 Box-Cox Transformation; 4.8 Binning; 4.8.1 Bucket Method; 4.8.2 Analytical Binning for Nominal Variables; 4.8.3 Quantiles; 4.8.4 Binning in Practice; 4.9 Timing Considerations; 4.10 Operational Issues. | |
| 500 | |a 5 Analytics. | ||
| 520 | |a Data mining is well on its way to becoming a recognized discipline in the overlapping areas of IT, statistics, machine learning, and AI. Practical Data Mining for Business presents a user-friendly approach to data mining methods, covering the typical uses to which it is applied. The methodology is complemented by case studies to create a versatile reference book, allowing readers to look for specific methods as well as for specific applications. The book is formatted to allow statisticians, computer scientists, and economists to cross-reference from a particular application or method. | ||
| 504 | |a Includes bibliographical references and index. | ||
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Data mining. | |
| 650 | 0 | |a Marketing |x Data processing. | |
| 650 | 0 | |a Management |x Mathematical models. | |
| 650 | 2 | |a Data Mining | |
| 650 | 6 | |a Exploration de données (Informatique) | |
| 650 | 6 | |a Marketing |x Informatique. | |
| 650 | 6 | |a Gestion |x Modèles mathématiques. | |
| 650 | 7 | |a Data mining |2 fast | |
| 650 | 7 | |a Management |x Mathematical models |2 fast | |
| 650 | 7 | |a Marketing |x Data processing |2 fast | |
| 700 | 1 | |a Coleman, Shirley. | |
| 758 | |i has work: |a A Practical Guide to Data Mining for Business and Industry [electronic resource] (Work) |1 https://id.oclc.org/worldcat/entity/E39PCY8mqtvGwHJXwpqCKRk4FX |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |a Ahlemeyer-Stubbe, Andrea. |t A Practical Guide to Data Mining for Business and Industry. |d Hoboken : Wiley, ©2014 |z 9781119977131 |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=1658813 |z Texto completo |
| 938 | |a Coutts Information Services |b COUT |n 26998117 | ||
| 938 | |a EBL - Ebook Library |b EBLB |n EBL1658813 | ||
| 938 | |a Recorded Books, LLC |b RECE |n rbeEB00316109 | ||
| 994 | |a 92 |b IZTAP | ||