Data Mining Techniques : For Marketing, Sales, and Customer Relationship Management 🔍
Michael J. Berry, Gordon S. Linoff
John Wiley and Sons, 3rd ed., Indianapolis, IN, Indiana, 2011
英语 [en] · EPUB · 25.7MB · 2011 · 📘 非小说类图书 · 🚀/lgli/lgrs/nexusstc/upload/zlib · Save
描述
The leading introductory book on data mining, fully updated and revised! When Berry and Linoff wrote the first edition of Data Mining Techniques in the late 1990s, data mining was just starting to move out of the lab and into the office and has since grown to become an indispensable tool of modern business. This new edition--more than 50% new and revised-- is a significant update from the previous one, and shows you how to harness the newest data mining methods and techniques to solve common business problems. The duo of unparalleled authors share invaluable advice for improving response rates to direct marketing campaigns, identifying new customer segments, and estimating credit risk. In addition, they cover more advanced topics such as preparing data for analysis and creating the necessary infrastructure for data mining at your company. Features significant updates since the previous edition and updates you on best practices for using data mining methods and techniques for solving common business problems Covers a new data mining technique in every chapter along with clear, concise explanations on how to apply each technique immediately Touches on core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, survival analysis, and more Provides best practices for performing data mining using simple tools such as Excel Data Mining Techniques, Third Edition covers a new data mining technique with each successive chapter and then demonstrates how you can apply that technique for improved marketing, sales, and customer support to get immediate results.Exercises and data sets to accompany this book are available at jmp.com/en_us/academic/data-mining-techniques.html
备用文件名
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备用文件名
zlib/Business & Economics/Sales & Marketing/Michael J. Berry, Gordon S. Linoff/Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management_1128140.epub
备选作者
Linoff, Gordon S., Berry, Michael J. A.
备选作者
Gordon S. Linoff; Michael J. A. Berry
备用出版商
Wiley Computer Publishing [Imprint] John Wiley & Sons, Incorporated
备用出版商
Spectrum Publications
备用出版商
Halsted Press
备用版本
John Wiley & Sons, Inc., Indianapolis, Ind, 2011
备用版本
United States, United States of America
备用版本
3rd ed, Indianapolis, IN, cop. 2011
备用版本
3rd ed, Hoboken, April 2011
备用版本
Hoboken, N.J, 2013
备用版本
3, 2011-03-23
元数据中的注释
до 2011-08
元数据中的注释
lg689293
元数据中的注释
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元数据中的注释
Berry's name appears first on the 2nd ed.
Includes index.
Includes index.
备用描述
<p>The leading introductory book on data mining, fully updated and revised!</p>
<p>When Berry and Linoff wrote the first edition of <i>Data Mining Techniques</i> in the late 1990s, data mining was just starting to move out of the lab and into the office and has since grown to become an indispensable tool of modern business. This new edition—more than 50% new and revised— is a significant update from the previous one, and shows you how to harness the newest data mining methods and techniques to solve common business problems. The duo of unparalleled authors share invaluable advice for improving response rates to direct marketing campaigns, identifying new customer segments, and estimating credit risk. In addition, they cover more advanced topics such as preparing data for analysis and creating the necessary infrastructure for data mining at your company. </p>
<ul>
<li>Features significant updates since the previous edition and updates you on best practices for using data mining methods and techniques for solving common business problems</li>
<li>Covers a new data mining technique in every chapter along with clear, concise explanations on how to apply each technique immediately</li>
<li>Touches on core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, survival analysis, and more</li>
<li>Provides best practices for performing data mining using simple tools such as Excel</li>
</ul>
<p><i>Data Mining Techniques, Third Edition</i> covers a new data mining technique with each successive chapter and then demonstrates how you can apply that technique for improved marketing, sales, and customer support to get immediate results.</p>
<p>When Berry and Linoff wrote the first edition of <i>Data Mining Techniques</i> in the late 1990s, data mining was just starting to move out of the lab and into the office and has since grown to become an indispensable tool of modern business. This new edition—more than 50% new and revised— is a significant update from the previous one, and shows you how to harness the newest data mining methods and techniques to solve common business problems. The duo of unparalleled authors share invaluable advice for improving response rates to direct marketing campaigns, identifying new customer segments, and estimating credit risk. In addition, they cover more advanced topics such as preparing data for analysis and creating the necessary infrastructure for data mining at your company. </p>
<ul>
<li>Features significant updates since the previous edition and updates you on best practices for using data mining methods and techniques for solving common business problems</li>
<li>Covers a new data mining technique in every chapter along with clear, concise explanations on how to apply each technique immediately</li>
<li>Touches on core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, survival analysis, and more</li>
<li>Provides best practices for performing data mining using simple tools such as Excel</li>
</ul>
<p><i>Data Mining Techniques, Third Edition</i> covers a new data mining technique with each successive chapter and then demonstrates how you can apply that technique for improved marketing, sales, and customer support to get immediate results.</p>
备用描述
<p>The leading introductory book on data mining, fully updated and revised!<br></p><p>When Berry and Linoff wrote the first edition of Data Mining Techniques in the late 1990s, data mining was just starting to move out of the lab and into the office and has since grown to become an indispensable tool of modern business. This new edition—more than 50% new and revised—is a significant update from the previous one, and shows you how to harness the newest data mining methods and techniques to solve common business problems. The duo of unparalleled authors share invaluable advice for improving response rates to direct marketing campaigns, identifying new customer segments, and estimating credit risk. In addition, they cover more advanced topics such as preparing data for analysis and creating the necessary infrastructure for data mining at your company.<br></p><ul> <li>Features significant updates since the previous edition and updates you on best practices for using data mining methods and techniques for solving common business problems </li> <li>Covers a new data mining technique in every chapter along with clear, concise explanations on how to apply each technique immediately </li> <li>Touches on core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, survival analysis, and more </li> <li>Provides best practices for performing data mining using simple tools such as Excel </li></ul><p>Data Mining Techniques, Third Edition covers a new data mining technique with each successive chapter and then demonstrates how you can apply that technique for improved marketing, sales, and customer support to get immediate results.<br></p>
备用描述
Annotation The leading introductory book on data mining, fully updated and revised!When Berry and Linoff wrote the first edition of Data Mining Techniques in the late 1990s, data mining was just starting to move out of the lab and into the office and has since grown to become an indispensable tool of modern business. This new editionmore than 50% new and revisedis a significant update from the previous one, and shows you how to harness the newest data mining methods and techniques to solve common business problems. The duo of unparalleled authors share invaluable advice for improving response rates to direct marketing campaigns, identifying new customer segments, and estimating credit risk. In addition, they cover more advanced topics such as preparing data for analysis and creating the necessary infrastructure for data mining at your company. Features significant updates since the previous edition and updates you on best practices for using data mining methods and techniques for solving common business problemsCovers a new data mining technique in every chapter along with clear, concise explanations on how to apply each technique immediatelyTouches on core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, survival analysis, and moreProvides best practices for performing data mining using simple tools such as ExcelData Mining Techniques, Third Edition covers a new data mining technique with each successive chapter and then demonstrates how you can apply that technique for improved marketing, sales, and customer support to get immediate results
开源日期
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Anna’s Archive Container identifier.
AacId:
aacid__worldcat__20250804T000000Z__VBTw44Z68ny7wVbCTSiR7w
Anna’s Archive Container identifier.
AacId:
aacid__worldcat__20250804T000000Z__VEccudxUdWjoSvL3Dz2K6X
Anna’s Archive Container identifier.
AacId:
aacid__worldcat__20250804T000000Z__VSomtgrKA2S5KL4LZGJX2H
Anna’s Archive Container identifier.
AacId:
aacid__worldcat__20250804T000000Z__a2XBiR26qBewtzoR5mxPZr
Anna’s Archive Container identifier.
AacId:
aacid__worldcat__20250804T000000Z__eGNRb9dQQRajSDf89c97GB
Anna’s Archive Container identifier.
AacId:
aacid__worldcat__20250804T000000Z__f5aaZTRiigwNKKDDXkYgMS
Anna’s Archive Container identifier.
AacId:
aacid__worldcat__20250804T000000Z__mWeTY53r7hZovvxvB32nVQ
Anna’s Archive Container identifier.
AacId:
aacid__zlib3_records__20240809T181636Z__1128140__hc25VLbLhMXY6NWxMrW9Y9
Anna’s Archive Container identifier.
AA Record ID:
md5:d542e0f248bc281d772e2a4d930df32a
Anna’s Archive record ID.
Collection:
lgli
The collection on Anna’s Archive that provided data for this record.
URL: /datasets/lgli
网站: /datasets
代码浏览器: 在代码浏览器中查看“collection:lgli”
Collection:
lgrs
The collection on Anna’s Archive that provided data for this record.
URL: /datasets/lgrs
网站: /datasets
代码浏览器: 在代码浏览器中查看“collection:lgrs”
Collection:
nexusstc
The collection on Anna’s Archive that provided data for this record.
URL: /datasets/nexusstc
网站: /datasets
Collection:
upload
The collection on Anna’s Archive that provided data for this record.
URL: /datasets/upload
网站: /datasets
代码浏览器: 在代码浏览器中查看“collection:upload”
Collection:
zlib
The collection on Anna’s Archive that provided data for this record.
URL: /datasets/zlib
网站: /datasets
代码浏览器: 在代码浏览器中查看“collection:zlib”
Content Type:
book_nonfiction
Content type, determined by Anna’s Archive.
SHA-256:
75f9d4d2
代码浏览器: 在代码浏览器中查看“crc32:75f9d4d2”
EBSCOhost eBook Index Source Scrape Date:
2024-08-23
Date Anna’s Archive scraped the EBSCOhost metadata.
网站: /datasets/edsebk
Google Books Source Scrape Date:
2024-09-20
Date Anna’s Archive scraped the Google Books collection.
网站: /datasets/gbooks
ISBNdb Scrape Date:
2022-09-01
The date that Anna’s Archive scraped this ISBNdb record.
网站: /datasets/isbndb
ISBN GRP Source Scrape Date:
2024-09-20
Date Anna’s Archive scraped the ISBN GRP collection.
Libgen.rs Non-Fiction Date:
2011-08-31
Date Libgen.rs Non_Fiction published this file.
网站: /datasets/lgrs
Libby Source Scrape Date:
2024-09-11
Date Anna’s Archive scraped the Libby collection.
网站: /datasets/libby
Nexus/STC Source issued_at Date:
2011-01-01
Date Nexus/STC reports in their issued_at field, which is the “issuing time of the item described by record.”
Nexus/STC Source Updated Date:
2024-05-16
Date Nexus/STC last updated this record.
OCLC Scrape Date:
2025-01-01
The date that Anna’s Archive scraped this OCLC/WorldCat record.
网站: /datasets/oclc
OpenLib 'created' Date:
2011-10-22
The 'created' metadata field on the Open Library, indicating when the first version of this record was created.
网站: /datasets/ol
Upload Collection Record Date:
2025-10-27
Date Anna’s Archive indexed this file in our 'upload' collection.
网站: /datasets/upload
EBSCOhost eBook Index Accession Number:
520245
ID in the EBSCOhost eBook Index (edsebk).
网站: /datasets/edsebk
代码浏览器: 在代码浏览器中查看“edsebk:520245”
EBSCOhost eBook Index Subject:
bisac/COMPUTERS / Data Science / Data Warehousing
Tag in EBSCOhost eBook Index.
网站: /datasets/edsebk
EBSCOhost eBook Index Subject:
unclass/Business--Data processing
Tag in EBSCOhost eBook Index.
网站: /datasets/edsebk
EBSCOhost eBook Index Subject:
unclass/Data mining
Tag in EBSCOhost eBook Index.
网站: /datasets/edsebk
EBSCOhost eBook Index Subject:
unclass/Management--Data processing
Tag in EBSCOhost eBook Index.
网站: /datasets/edsebk
EBSCOhost eBook Index Subject:
unclass/Marketing--Data processing
Tag in EBSCOhost eBook Index.
网站: /datasets/edsebk
Filepath:
lgli/_422093.d542e0f248bc281d772e2a4d930df32a.epub
Browse collections using their original file paths (particularly 'upload' is interesting)
Filepath:
lgrsnf/_422093.d542e0f248bc281d772e2a4d930df32a.epub
Browse collections using their original file paths (particularly 'upload' is interesting)
Filepath:
nexusstc/Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management/d542e0f248bc281d772e2a4d930df32a.epub
Browse collections using their original file paths (particularly 'upload' is interesting)
Filepath:
upload/newsarch_ebooks_2025_10/2020/11/27/0470650931.epub
Browse collections using their original file paths (particularly 'upload' is interesting)
Filepath:
zlib/Business & Economics/Sales & Marketing/Michael J. Berry, Gordon S. Linoff/Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management_1128140.epub
Browse collections using their original file paths (particularly 'upload' is interesting)
Filesize:
25701317
Filesize in bytes.
Google Books:
wK5JDwAAQBAJ
网站: /datasets/gbooks
IPFS CID:
QmWYKTN8TrsajN82peeo7G8YkRJrqMxQD9yK2uk3iaijhv
Content Identifier (CID) of the InterPlanetary File System (IPFS).
IPFS CID:
bafykbzacebh3ncyibbpqfa64kaggohx5t2kcteavutjqixafcxmdurxb2b25k
Content Identifier (CID) of the InterPlanetary File System (IPFS).
ISBN GRP ID:
78eee76d99628986e177e6fdcfecd995
ISBN GRP ID.
ISBN GRP ID:
7cda57a3796425716d9feeb3cf0817cc
ISBN GRP ID.
ISBN GRP ID:
9f31d739192519b3dd32246b3a506350
ISBN GRP ID.
LCC:
HF5415.125 .B47 2011
Library of Congress Classification
LCC:
HF5415.125 .L56 2011eb
Library of Congress Classification
Libgen.li File:
91770017
Global file ID in Libgen.li. Directly taken from the 'f_id' field in the 'files' table.
网站: /datasets/lgli
代码浏览器: 在代码浏览器中查看“lgli:91770017”
Libgen.li libgen_id:
689293
Repository ID for the 'libgen' repository in Libgen.li. Directly taken from the 'libgen_id' field in the 'files' table. Corresponds to the 'thousands folder' torrents.
网站: /datasets/lgli
Libgen.rs Non-Fiction:
689293
Repository ID for the non-fiction ('libgen') repository in Libgen.rs. Directly taken from the 'id' field in the 'updated' table. Corresponds to the 'thousands folder' torrents.
网站: /datasets/lgrs
代码浏览器: 在代码浏览器中查看“lgrsnf:689293”
MD5:
d542e0f248bc281d772e2a4d930df32a
Nexus/STC:
b9fchb46n5dlizyxdcm8jvhik
ID of an individual edition of a file in Nexus/STC.
IA:
dataminingtechni0000lino
OCLC 'From Filename':
2023_04_v3/1218/1218495578
网站: /datasets/oclc
OCLC 'From Filename':
2023_04_v3/1911/19116086
网站: /datasets/oclc
OCLC 'From Filename':
2023_04_v3/2827/282717876
网站: /datasets/oclc
OCLC 'From Filename':
2023_04_v3/4407/440759629
网站: /datasets/oclc
OCLC 'From Filename':
2023_04_v3/6817/681793503
网站: /datasets/oclc
OCLC 'From Filename':
2023_04_v3/7455/745594164
网站: /datasets/oclc
OCLC 'From Filename':
2023_04_v3/8613/861351364
网站: /datasets/oclc
OCLC 'From Filename':
2023_05_v4_type123/1197/1197278462
网站: /datasets/oclc
OCLC 'From Filename':
2023_05_v4_type123/1636/163625345
网站: /datasets/oclc
OCLC 'From Filename':
2023_05_v4_type123/2740/274033227
网站: /datasets/oclc
OCLC 'From Filename':
2023_05_v4_type123/4708/470833601
网站: /datasets/oclc
OCLC 'From Filename':
2023_05_v4_type123/5931/593113008
网站: /datasets/oclc
OCLC 'From Filename':
2023_05_v4_type123/7984/79848415
网站: /datasets/oclc
OCLC 'From Filename':
2023_05_v4_type123/7988/798868754
网站: /datasets/oclc
OCLC 'From Filename':
range_query/6613663###
网站: /datasets/oclc
OCLC 'From Filename':
search_editions_response/36755821
网站: /datasets/oclc
OCLC 'From Filename':
search_editions_response/465865332
网站: /datasets/oclc
OCLC 'From Filename':
t123/1031/1031548002
网站: /datasets/oclc
OCLC 'From Filename':
w2/v6/1070/1070964888
网站: /datasets/oclc
OCLC 'From Filename':
w2/v6/1228/1228993640
网站: /datasets/oclc
OCLC 'From Filename':
w2/v7/1112/1112793635
网站: /datasets/oclc
OCLC 'From Filename':
w2/v7/1114/1114637561
网站: /datasets/oclc
OCLC 'From Filename':
w2/v7/1133/1133509173
网站: /datasets/oclc
OCLC 'From Filename':
w2/v7/1139/1139870301
网站: /datasets/oclc
OCLC 'From Filename':
w2/v7/1228/1228604438
网站: /datasets/oclc
OCLC 'From Filename':
w2/v7/1229/1229875151
网站: /datasets/oclc
OCLC 'From Filename':
w2/v7/1280/1280758105
网站: /datasets/oclc
OCLC 'From Filename':
w2/v7/1815/181541498
网站: /datasets/oclc
OCLC 'From Filename':
w2/v7/2827/282776263
网站: /datasets/oclc
OCLC 'From Filename':
w2/v7/3053/305351787
网站: /datasets/oclc
OCLC 'From Filename':
w2/v7/3198/319875719
网站: /datasets/oclc
OCLC 'From Filename':
w2/v7/4047/404793426
网站: /datasets/oclc
OCLC 'From Filename':
w2/v7/4200/420085059
网站: /datasets/oclc
OCLC 'From Filename':
w2/v7/4901/490149643
网站: /datasets/oclc
OCLC 'From Filename':
w2/v7/4907/490765206
网站: /datasets/oclc
OCLC 'From Filename':
w2/v7/5048/504814655
网站: /datasets/oclc
OCLC 'From Filename':
w2/v7/5052/505250459
网站: /datasets/oclc
OCLC 'From Filename':
w2/v7/5239/523982959
网站: /datasets/oclc
OCLC 'From Filename':
w2/v7/5479/547910292
网站: /datasets/oclc
OCLC 'From Filename':
w2/v7/6408/640840857
网站: /datasets/oclc
OCLC 'From Filename':
w2/v7/6808/680843317
网站: /datasets/oclc
OCLC 'From Filename':
w2/v7/7039/703901688
网站: /datasets/oclc
OCLC 'From Filename':
w2/v7/7329/732937795
网站: /datasets/oclc
OCLC 'From Filename':
w2/v7/8225/822582257
网站: /datasets/oclc
OCLC 'From Filename':
w2/v7/9096/909624079
网站: /datasets/oclc
OCLC 'From Filename':
w2/v8/1069/1069871590
网站: /datasets/oclc
OCLC 'From Filename':
worldcat_2022_09_titles_1_backup_2022_10_12/v3/0131/13145755
网站: /datasets/oclc
OCLC 'From Filename':
worldcat_2022_09_titles_1_backup_2022_10_12/v3/0743/74386077
网站: /datasets/oclc
OCLC 'From Filename':
worldcat_2022_09_titles_1_backup_2022_10_12/v3/0772/77270342
网站: /datasets/oclc
OCLC 'From Filename':
worldcat_2022_09_titles_1_backup_2022_10_12/v3/0782/78279901
网站: /datasets/oclc
OCLC 'From Filename':
worldcat_2022_09_titles_1_backup_2022_10_12/v3/0806/80609257
网站: /datasets/oclc
OCLC 'From Filename':
worldcat_2022_09_titles_1_backup_2022_10_12/v3/0864/86413928
网站: /datasets/oclc
OCLC 'From Filename':
worldcat_2022_09_titles_1_backup_2022_10_12/v3/0991/99192238
网站: /datasets/oclc
OCLC 'From Filename':
worldcat_2022_09_titles_1_backup_2022_10_12/v3/0993/99336787
网站: /datasets/oclc
OCLC 'From Filename':
worldcat_2022_09_titles_1_backup_2022_10_12/v3/0999/99940789
网站: /datasets/oclc
OCLC 'From Filename':
worldcat_2022_09_titles_1_backup_2022_10_12/v3/1060/106051973
网站: /datasets/oclc
OCLC 'From Filename':
worldcat_2022_09_titles_1_backup_2022_10_12/v3/1148/114899102
网站: /datasets/oclc
OCLC 'From Filename':
worldcat_2022_09_titles_1_backup_2022_10_12/v3/1165/116538726
网站: /datasets/oclc
OCLC 'From Filename':
worldcat_2022_09_titles_1_backup_2022_10_12/v6/1148/1148346839
网站: /datasets/oclc
OCLC 'From Filename':
worldcat_2022_09_titles_1_backup_2022_10_12/v6/1293/1293616489
网站: /datasets/oclc
Open Library:
OL16147010W
代码浏览器: 在代码浏览器中查看“ol:OL16147010W”
Open Library:
OL25029407M
代码浏览器: 在代码浏览器中查看“ol:OL25029407M”
Open Library Source Record:
bwb:9780470650936
The code for a source record that Open Library imported from.
网站: /datasets/ol
Open Library Source Record:
bwb:9781118087459
The code for a source record that Open Library imported from.
网站: /datasets/ol
Open Library Source Record:
bwb:9781118087473
The code for a source record that Open Library imported from.
网站: /datasets/ol
Open Library Source Record:
bwb:9781118087503
The code for a source record that Open Library imported from.
网站: /datasets/ol
Open Library Source Record:
harvard_bibliographic_metadata/ab.bib.13.20150123.full.mrc:381957290:2062
The code for a source record that Open Library imported from.
网站: /datasets/ol
Open Library Source Record:
ia:dataminingtechni0000lino
The code for a source record that Open Library imported from.
网站: /datasets/ol
Open Library Source Record:
idb:9780470650936
The code for a source record that Open Library imported from.
网站: /datasets/ol
Open Library Source Record:
marc_columbia/Columbia-extract-20221130-025.mrc:28018664:3168
The code for a source record that Open Library imported from.
URL: https://openlibrary.org/show-records/marc_columbia/Columbia-extract-20221130-025.mrc:28018664:3168
网站: /datasets/ol
Open Library Source Record:
marc_loc_2016/BooksAll.2016.part39.utf8:154732107:1005
The code for a source record that Open Library imported from.
网站: /datasets/ol
Open Library Source Record:
marc_loc_updates/v39.i37.records.utf8:15753152:1005
The code for a source record that Open Library imported from.
网站: /datasets/ol
Open Library Source Record:
promise:bwb_daily_pallets_2022-05-25
The code for a source record that Open Library imported from.
网站: /datasets/ol
Server Path:
g4/libgenrs_nonfiction/libgenrs_nonfiction/689000/d542e0f248bc281d772e2a4d930df32a
Path on Anna’s Archive partner servers.
SHA-1:
a6d894185a0a01e0b037e323bb8436535ae2cc31
SHA-1:
u3mjigc2bia6bmbx4mr3xbbwknnoftbr
SHA-256:
181ac14936a5f0fa54656df3adb0f027ce46aa7942304150163bb21997111ebd
Torrent:
external/libgen_rs_non_fic/r_689000.torrent
Bulk torrent for long-term preservation.
网站: /torrents
Z-Library:
1128140
ID in Z-Library.
URL: https://z-lib.gd/
网站: /datasets/zlib
代码浏览器: 在代码浏览器中查看“zlib:1128140”
Zlib Category ID:
114
Category ID on the Z-Library website.
Zlib Category Name:
Business & Economics/Sales & Marketing
Name for the zlib_category_id (category ID on the Z-Library website).
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