Data mining and analysis: fundamental concepts and algorithms
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Cambridge Univ. Press
2014
|
| Ausgabe: | 1. publ. |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Includes bibliographical references and index. Hier auch später erschienene, unveränderte Nachdrucke |
| Beschreibung: | XI, 593 S. graph. Darst. |
| ISBN: | 9780521766333 |
Internformat
MARC
| LEADER | 00000nam a2200000 c 4500 | ||
|---|---|---|---|
| 001 | BV041837190 | ||
| 003 | DE-604 | ||
| 005 | 20190709 | ||
| 007 | t | ||
| 008 | 140509s2014 d||| |||| 00||| eng d | ||
| 010 | |a 2013037544 | ||
| 020 | |a 9780521766333 |c hardback |9 978-0-521-76633-3 | ||
| 035 | |a (OCoLC)886622554 | ||
| 035 | |a (DE-599)GBV768495768 | ||
| 040 | |a DE-604 |b ger |e aacr | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-473 |a DE-29T |a DE-11 |a DE-703 |a DE-859 |a DE-739 |a DE-1050 |a DE-945 |a DE-862 |a DE-1102 |a DE-521 | ||
| 082 | 0 | |a 006.312 | |
| 084 | |a ST 530 |0 (DE-625)143679: |2 rvk | ||
| 100 | 1 | |a Zaki, Mohammed J. |d 1971- |e Verfasser |0 (DE-588)121766799 |4 aut | |
| 245 | 1 | 0 | |a Data mining and analysis |b fundamental concepts and algorithms |c Mohammed J. Zaki ; Wagner Meira |
| 250 | |a 1. publ. | ||
| 264 | 1 | |a New York, NY |b Cambridge Univ. Press |c 2014 | |
| 300 | |a XI, 593 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 500 | |a Includes bibliographical references and index. Hier auch später erschienene, unveränderte Nachdrucke | ||
| 650 | 0 | 7 | |a Data Mining |0 (DE-588)4428654-5 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Data Mining |0 (DE-588)4428654-5 |D s |
| 689 | 0 | |5 DE-604 | |
| 700 | 1 | |a Meira, Wagner |d 1967- |e Verfasser |0 (DE-588)1054618275 |4 aut | |
| 856 | 4 | 2 | |m Digitalisierung UB Bamberg - ADAM Catalogue Enrichment |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027281929&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-027281929 | ||
Datensatz im Suchindex
| DE-BY-862_location | 2000 |
|---|---|
| DE-BY-FWS_call_number | 2000/ST 530 Z21 |
| DE-BY-FWS_katkey | 627899 |
| DE-BY-FWS_media_number | 083000515979 |
| _version_ | 1806176621106823168 |
| adam_text | Contents
Preface
page
ix
1
Data Mining and Analysis
.......................... 1
1.1
Data Matrix
1
1.2
Attributes
3
1.3
Data: Algebraic and Geometric View
4
1.4
Data: Probabilistic View
14
1.5
Data Mining
25
1.6
Further Reading
30
1.7
Exercises
30
PART ONE: DATA ANALYSIS FOUNDATIONS
2
Numeric Attributes
............................. 33
2.1
Univariate Analysis
33
2.2
Bivariate Analysis
42
2.3
Muitivariate Analysis
48
2.4
Data Normalization
52
2.5
Normal Distribution
54
2.6
Further Reading
60
2.7
Exercises
60
3
Categorical Attributes
............................ 63
3.1
Univariate Analysis
63
3.2
Bivariate Analysis
72
3.3
Muitivariate Analysis
82
3.4
Distance and Angle
87
3.5
Discretization
89
3.6
Further Reading
91
3.7
Exercises
91
4
Graph Data
................................. 93
4.1
Graph Concepts
93
4.2
Topological Attributes
97
Contents
VI
4.3 Centrality
Analysis
4.4 Graph Models 112
4.5
Further Reading 132
4.6
Exercises
Kernel
Methods
............................... 134
5.1 Kernel Matrix l38
5.2
Vector
Kernels 144
5.3 Basic Kernel
Operations in
Feature Space 148
5.4 Kernels
for Complex Objects
154
5.5
Further Reading
161
5.6
Exercises
6
High-dimensional Data
........................... 163
6.1
High-dimensional Objects
163
6.2
High-dimensional Volumes
165
6.3
Hypersphere Inscribed within Hypercube
168
6.4
Volume of Thin Hypersphere Shell
169
6.5
Diagonals in Hyperspace
171
6.6
Density of the Multivariate Normal
172
6.7
Appendix: Derivation of Hypersphere Volume
175
6.8
Further Reading
180
6.9
Exercises
180
7
Dimensionality Reduction
......................... 183
7.1
Background
183
7.2
Principal Component Analysis
187
7.3
Kernel Principal Component Analysis
202
7.4
Singular Value Decomposition
208
7.5
Further Reading
213
7.6
Exercises
214
PART TWO: FREQUENT PATTERN MINING
8
Itemset Mining
............................... 217
8.1
Frequent Itemsets and Association Rules
217
8.2
Itemset Mining Algorithms
221
8.3
Generating Association Rules
234
8.4
Further Reading
236
8.5
Exercises
237
9
Summarizing Itemsets
........................... 242
9.1
Maximal and Closed Frequent Itemsets
242
9.2
Mining Maximal Frequent Itemsets: GenMax Algorithm
245
9.3
Mining Closed Frequent Itemsets: Charm Algorithm
248
9.4
Nonderivable Itemsets
250
9.5
Further Reading
25л
9.6
Exercises
256
Contents
vii
10
Sequence
Mining.............................. 259
10.1
Frequent Sequences
259
10.2
Mining Frequent Sequences
260
10.3
Substring Mining via Suffix Trees
267
10.4
Further Reading
277
10.5
Exercises
277
11
Graph Pattern Mining
............................ 280
11.1
Isomorphism and Support
280
11.2
Candidate Generation
284
11.3
The gSpan Algorithm
288
11.4
Further Reading
296
11.5
Exercises
297
12
Pattern and Rule Assessment
........................ 301
12.1
Rule and Pattern Assessment Measures
301
12.2
Significance Testing and Confidence Intervals
316
12.3
Further Reading
328
12.4
Exercises
328
PART THREE: CLUSTERING
13
Representative-based Clustering
...................... 333
13.1
K-means Algorithm
333
13.2
Kernel K-means
338
13.3
Expectation-Maximization Clustering
342
13.4
Further Reading
360
13.5
Exercises
361
14
Hierarchical Clustering
........................... 364
14.1
Preliminaries
364
14.2
Agglomerative Hierarchical Clustering
366
14.3
Further Reading
372
14.4
Exercises and Projects
373
15
Density-based Clustering
.......................... 375
15.1
The DBSCAN Algorithm
375
15.2
Kernel Density Estimation
379
15.3
Density-based Clustering: DENCLUE
385
15.4
Further Reading
390
15.5
Exercises
391
16
Spectral and Graph Clustering
....................... 394
16.1
Graphs and Matrices
394
16.2
Clustering as Graph Cuts
401
16.3
Markov Clustering
416
16.4
Further Reading
422
16.5
Exercises
423
Contents
viii
425
17
Clustering
Validation
............................
17.1
External Measures ^
17.2
Internal Measures
448
17.3
Relative Measures
17.4
Further Reading 46i
17.5
Exercises
PART FOUR: CLASSIFICATION
18
Probabilistic Classification
.........................
467
18.1
Bayes
Classifier 467
18.2
Naive
Bayes
Classifier 473
18.3
^Nearest Neighbors Classifier 477
18.4
Further Reading 479
18.5
Exercises 479
19
Decision Tree Classifier
. . . ,....................... 481
19.1
Decision Trees
483
19.2
Decision Tree Algorithm
485
19.3
Further Reading
496
19.4
Exercises
496
20
Linear Discriminant Analysis
........................ 498
20.1
Optimal Linear Discriminant
498
20.2
Kernel Discriminant Analysis
505
20.3
Further Reading
511
20.4
Exercises
512
21
Support Vector Machines
.......................... 514
21.1
Support Vectors and Margins
514
21.2
SVM: Linear and Separable Case
520
21.3
Soft Margin SVM: Linear and Nonseparable Case
524
21.4
Kernel SVM: Nonlinear Case
530
21.5
SVM Training Algorithms
534
21.6
Further Reading
545
21.7
Exercises
545
22
Classification Assessment
................. 548
22.1
Classification Performance Measures
548
22.2
Classifier Evaluation
562
22.3
Bias-Variance Decomposition
572
22.4
Further Reading
22.5
Exercises
Index 585
|
| any_adam_object | 1 |
| author | Zaki, Mohammed J. 1971- Meira, Wagner 1967- |
| author_GND | (DE-588)121766799 (DE-588)1054618275 |
| author_facet | Zaki, Mohammed J. 1971- Meira, Wagner 1967- |
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| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.312 |
| dewey-search | 006.312 |
| dewey-sort | 16.312 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| edition | 1. publ. |
| format | Book |
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| id | DE-604.BV041837190 |
| illustrated | Illustrated |
| indexdate | 2024-08-01T11:24:14Z |
| institution | BVB |
| isbn | 9780521766333 |
| language | English |
| lccn | 2013037544 |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-027281929 |
| oclc_num | 886622554 |
| open_access_boolean | |
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| owner_facet | DE-473 DE-BY-UBG DE-29T DE-11 DE-703 DE-859 DE-739 DE-1050 DE-945 DE-862 DE-BY-FWS DE-1102 DE-521 |
| physical | XI, 593 S. graph. Darst. |
| publishDate | 2014 |
| publishDateSearch | 2014 |
| publishDateSort | 2014 |
| publisher | Cambridge Univ. Press |
| record_format | marc |
| spellingShingle | Zaki, Mohammed J. 1971- Meira, Wagner 1967- Data mining and analysis fundamental concepts and algorithms Data Mining (DE-588)4428654-5 gnd |
| subject_GND | (DE-588)4428654-5 |
| title | Data mining and analysis fundamental concepts and algorithms |
| title_auth | Data mining and analysis fundamental concepts and algorithms |
| title_exact_search | Data mining and analysis fundamental concepts and algorithms |
| title_full | Data mining and analysis fundamental concepts and algorithms Mohammed J. Zaki ; Wagner Meira |
| title_fullStr | Data mining and analysis fundamental concepts and algorithms Mohammed J. Zaki ; Wagner Meira |
| title_full_unstemmed | Data mining and analysis fundamental concepts and algorithms Mohammed J. Zaki ; Wagner Meira |
| title_short | Data mining and analysis |
| title_sort | data mining and analysis fundamental concepts and algorithms |
| title_sub | fundamental concepts and algorithms |
| topic | Data Mining (DE-588)4428654-5 gnd |
| topic_facet | Data Mining |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027281929&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT zakimohammedj dataminingandanalysisfundamentalconceptsandalgorithms AT meirawagner dataminingandanalysisfundamentalconceptsandalgorithms |
Inhaltsverzeichnis
Schweinfurt Zentralbibliothek Lesesaal
| Signatur: |
2000 ST 530 Z21 |
|---|---|
| Exemplar 1 | ausleihbar Checked out – Rückgabe bis: 31.12.2099 Vormerken |