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Applied data mining for business and industry 2nd ed

Applied data mining for business and industry 2nd ed (Loan 2 times)

Material type
단행본
Personal Author
Giudici, Paolo. Figini, Silvia.
Title Statement
Applied data mining for business and industry / Paolo Giudici, Silvia Figini.
판사항
2nd ed.
Publication, Distribution, etc
Chichester, U.K. :   Wiley ,   c2009.  
Physical Medium
viii, 249 p. : ill. ; 24 cm.
ISBN
9780470058862 (cloth) 0470058862 (cloth) 9780470058879 (pbk.) 0470058870 (pbk.)
Bibliography, Etc. Note
Includes bibliographical references (p. [237]-241) and index.
Subject Added Entry-Topical Term
Data mining. Business -- Data processing. Commercial statistics.
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001 000045558234
005 20091109162810
008 090224s2009 enka b 001 0 eng
010 ▼a 2009008334
020 ▼a 9780470058862 (cloth)
020 ▼a 0470058862 (cloth)
020 ▼a 9780470058879 (pbk.)
020 ▼a 0470058870 (pbk.)
035 ▼a (KERIS)REF000015224788
040 ▼a DLC ▼c DLC ▼d YDXCP ▼d BWKUK ▼d BWK ▼d CDX ▼d DLC ▼d 211009
050 0 0 ▼a QA76.9.D343 ▼b G75 2009
082 0 0 ▼a 005.74068 ▼2 22
090 ▼a 005.74068 ▼b G537a2
100 1 ▼a Giudici, Paolo.
245 1 0 ▼a Applied data mining for business and industry / ▼c Paolo Giudici, Silvia Figini.
250 ▼a 2nd ed.
260 ▼a Chichester, U.K. : ▼b Wiley , ▼c c2009.
300 ▼a viii, 249 p. : ▼b ill. ; ▼c 24 cm.
504 ▼a Includes bibliographical references (p. [237]-241) and index.
650 0 ▼a Data mining.
650 0 ▼a Business ▼x Data processing.
650 0 ▼a Commercial statistics.
700 1 ▼a Figini, Silvia.
945 ▼a KINS

Holdings Information

No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Main Library/Western Books/ Call Number 005.74068 G537a2 Accession No. 111552778 Availability Available Due Date Make a Reservation Service B M

Contents information

Table of Contents

1 Introduction.

Part I Methodology.

2 Organisation of the data.

2.1 Statistical units and statistical variables.

2.2 Data matrices and their transformations.

2.3 Complex data structures.

2.4 Summary.

3 Summary statistics.

3.1 Univariate exploratory analysis.

3.2 Bivariate exploratory analysis of quantitative data.

3.3 Multivariate exploratory analysis of quantitative data.

3.4 Multivariate exploratory analysis of qualitative data.

3.5 Reduction of dimensionality.

3.6 Further reading.

4 Model specification.

4.1 Measures of distance.

4.2 Cluster analysis.

4.3 Linear regression.

4.4 Logistic regression.

4.5 Tree models.

4.6 Neural networks.

4.7 Nearest-neighbour models.

4.8 Local models.

4.9 Uncertainty measures and inference.

4.10 Non-parametric modelling.

4.11 The normal linear model.

4.12 Generalised linear models.

4.13 Log-linear models.

4.14 Graphical models.

4..15 Survival analysis models.

4.16 Further reading.

5 Model evaluation.

5.1 Criteria based on statistical tests.

5.2 Criteria based on scoring functions.

5.3 Bayesian criteria.

5.4 Computational criteria.

5.5 Criteria based on loss functions.

5.6 Further reading.

Part II Business caste studies.

6 Describing website visitors.

6.1 Objectives of the analysis.

6.2 Description of the data.

6.3 Exploratory analysis.

6.4 Model building.

6.5 Model comparison.

6.6 Summary report.

7 Market basket analysis.

7.1 Objectives of the analysis.

7.2 Description of the data.

7.3 Exploratory data analysis.

7.4 Model building.

7.5 Model comparison.

7.6 Summary report.

8 Describing customer satisfaction.

8.1 Objectives of the analysis.

8.2 Description of the data.

8.3 Exploratory data analysis.

8.4 Model building.

8.5 Summary.

9 Predicting credit risk of small businesses.

9.1 Objectives of the analysis.

9.2 Description of the data.

9.3 Exploratory data analysis.

9.4 Model building.

9.5 Model comparison.

9.6 Summary report.

10 Predicting e-learning student performance.

10.1 Objectives of the analysis.

10.2 Description of the data.

10.3 Exploratory data analysis.

10.4 Model specification.

10.5 Model comparison.

10.6 Summary report.

11 Predicting customer lifetime value.

11.1 Objectives of the analysis.

11.2 Description of the data.

11.3 Exploratory data analysis.

11.4 Model specification.

11.5 Model comparison.

11.6 Summary report.

12 Operational risk management.

12.1 Context and objectives of the analysis.

12.2 Exploratory data analysis.

12.3 Model building.

12.4 Model comparison.

12.5 Summary conclusions.

References.

Index.


Information Provided By: : Aladin

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