語系:
繁體中文
English
說明(常見問題)
圖資館首頁
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Towards integrative machine learning...
~
(1998 :)
Towards integrative machine learning and knowledge extractionBIRS Workshop, Banff, AB, Canada, July 24-26, 2015 : revised selected papers /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Towards integrative machine learning and knowledge extractionedited by Andreas Holzinger ... [et al.].
其他題名:
BIRS Workshop, Banff, AB, Canada, July 24-26, 2015 : revised selected papers /
其他題名:
BIRS Workshop
其他作者:
Holzinger, Andreas.
團體作者:
出版者:
Cham :Springer International Publishing :2017.
面頁冊數:
xvi, 207 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
標題:
Data miningCongresses.
電子資源:
http://dx.doi.org/10.1007/978-3-319-69775-8
ISBN:
9783319697758$q(electronic bk.)
Towards integrative machine learning and knowledge extractionBIRS Workshop, Banff, AB, Canada, July 24-26, 2015 : revised selected papers /
Towards integrative machine learning and knowledge extraction
BIRS Workshop, Banff, AB, Canada, July 24-26, 2015 : revised selected papers /[electronic resource] :BIRS Workshopedited by Andreas Holzinger ... [et al.]. - Cham :Springer International Publishing :2017. - xvi, 207 p. :ill., digital ;24 cm. - Lecture notes in computer science,103440302-9743 ;. - Lecture notes in computer science ;4891..
Towards integrative Machine Learning & Knowledge Extraction -- Machine Learning and Knowledge Extraction in Digital Pathology needs an integrative approach -- Comparison of Public-Domain Software and Services for Probabilistic Record Linkage and Address Standardization -- Better Interpretable Models for Proteomics Data Analysis Using rule-based Mining -- Probabilistic Logic Programming in Action -- Persistent topology for natural data analysis -- A survey -- Predictive Models for Differentiation between Normal and Abnormal EEG through Cross-Correlation and Machine Learning Techniques -- A Brief Philosophical Note on Information -- Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline -- A Fast Semi-Automatic Segmentation Tool for Processing Brain Tumor Images -- Topological characteristics of oil and gas reservoirs and their applications -- Convolutional and Recurrent Neural Networks for Activity Recognition in Smart Environment.
The BIRS Workshop "Advances in Interactive Knowledge Discovery and Data Mining in Complex and Big Data Sets" (15w2181), held in July 2015 in Banff, Canada, was dedicated to stimulating a cross-domain integrative machine-learning approach and appraisal of "hot topics" toward tackling the grand challenge of reaching a level of useful and useable computational intelligence with a focus on real-world problems, such as in the health domain. This encompasses learning from prior data, extracting and discovering knowledge, generalizing the results, fighting the curse of dimensionality, and ultimately disentangling the underlying explanatory factors in complex data, i.e., to make sense of data within the context of the application domain. The workshop aimed to contribute advancements in promising novel areas such as at the intersection of machine learning and topological data analysis. History has shown that most often the overlapping areas at intersections of seemingly disparate fields are key for the stimulation of new insights and further advances. This is particularly true for the extremely broad field of machine learning.
ISBN: 9783319697758$q(electronic bk.)
Standard No.: 10.1007/978-3-319-69775-8doiSubjects--Topical Terms:
380776
Data mining
--Congresses.
LC Class. No.: QA76.9.D343
Dewey Class. No.: 006.312
Towards integrative machine learning and knowledge extractionBIRS Workshop, Banff, AB, Canada, July 24-26, 2015 : revised selected papers /
LDR
:03284nmm a2200349 a 4500
001
523406
003
DE-He213
005
20171028141530.0
006
m d
007
cr nn 008maaau
008
180628s2017 gw s 0 eng d
020
$a
9783319697758$q(electronic bk.)
020
$a
9783319697741$q(paper)
024
7
$a
10.1007/978-3-319-69775-8
$2
doi
035
$a
978-3-319-69775-8
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA76.9.D343
072
7
$a
UYQ
$2
bicssc
072
7
$a
TJFM1
$2
bicssc
072
7
$a
COM004000
$2
bisacsh
082
0 4
$a
006.312
$2
23
090
$a
QA76.9.D343
$b
B619 2015
111
2
$n
(3rd :
$d
1998 :
$c
Amsterdam, Netherlands)
$3
194767
245
1 0
$a
Towards integrative machine learning and knowledge extraction
$h
[electronic resource] :
$b
BIRS Workshop, Banff, AB, Canada, July 24-26, 2015 : revised selected papers /
$c
edited by Andreas Holzinger ... [et al.].
246
3
$a
BIRS Workshop
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2017.
300
$a
xvi, 207 p. :
$b
ill., digital ;
$c
24 cm.
490
1
$a
Lecture notes in computer science,
$x
0302-9743 ;
$v
10344
505
0
$a
Towards integrative Machine Learning & Knowledge Extraction -- Machine Learning and Knowledge Extraction in Digital Pathology needs an integrative approach -- Comparison of Public-Domain Software and Services for Probabilistic Record Linkage and Address Standardization -- Better Interpretable Models for Proteomics Data Analysis Using rule-based Mining -- Probabilistic Logic Programming in Action -- Persistent topology for natural data analysis -- A survey -- Predictive Models for Differentiation between Normal and Abnormal EEG through Cross-Correlation and Machine Learning Techniques -- A Brief Philosophical Note on Information -- Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline -- A Fast Semi-Automatic Segmentation Tool for Processing Brain Tumor Images -- Topological characteristics of oil and gas reservoirs and their applications -- Convolutional and Recurrent Neural Networks for Activity Recognition in Smart Environment.
520
$a
The BIRS Workshop "Advances in Interactive Knowledge Discovery and Data Mining in Complex and Big Data Sets" (15w2181), held in July 2015 in Banff, Canada, was dedicated to stimulating a cross-domain integrative machine-learning approach and appraisal of "hot topics" toward tackling the grand challenge of reaching a level of useful and useable computational intelligence with a focus on real-world problems, such as in the health domain. This encompasses learning from prior data, extracting and discovering knowledge, generalizing the results, fighting the curse of dimensionality, and ultimately disentangling the underlying explanatory factors in complex data, i.e., to make sense of data within the context of the application domain. The workshop aimed to contribute advancements in promising novel areas such as at the intersection of machine learning and topological data analysis. History has shown that most often the overlapping areas at intersections of seemingly disparate fields are key for the stimulation of new insights and further advances. This is particularly true for the extremely broad field of machine learning.
650
0
$a
Data mining
$v
Congresses.
$3
380776
650
0
$a
Machine learning.
$3
188639
650
0
$a
Human-computer interaction
$v
Congresses.
$3
384531
650
1 4
$a
Computer Science.
$3
212513
650
2 4
$a
Artificial Intelligence (incl. Robotics)
$3
252959
650
2 4
$a
Information Systems and Communication Service.
$3
274025
650
2 4
$a
Probability and Statistics in Computer Science.
$3
274053
650
2 4
$a
Software Engineering/Programming and Operating Systems.
$3
273711
650
2 4
$a
Computer Systems Organization and Communication Networks.
$3
273709
700
1
$a
Holzinger, Andreas.
$3
384530
710
2
$a
SpringerLink (Online service)
$3
273601
773
0
$t
Springer eBooks
830
0
$a
Lecture notes in computer science ;
$v
4891.
$3
383229
856
4 0
$u
http://dx.doi.org/10.1007/978-3-319-69775-8
950
$a
Computer Science (Springer-11645)
筆 0 讀者評論
全部
電子館藏
館藏
1 筆 • 頁數 1 •
1
條碼號
館藏地
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
000000147715
電子館藏
1圖書
電子書
EB QA76.9.D343 B619 2017
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
多媒體檔案
http://dx.doi.org/10.1007/978-3-319-69775-8
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼
登入