東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Towards integrative machine learning...

BIRS Workshop "Advances in Interactive Knowledge Discovery and Data Mining in Complex and Big Data Sets" ((2015 :)

FindBook

Google Book

Amazon

博客來

Towards integrative machine learning and knowledge extraction = BIRS 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 extraction/ edited 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:	BIRS Workshop "Advances in Interactive Knowledge Discovery and Data Mining in Complex and Big Data Sets"
出版者:	Cham :Springer International Publishing : : 2017.,
面頁冊數:	xvi, 207 p. :ill., digital ;24 cm.
內容註:	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.
Contained By:	Springer eBooks
標題:	Data mining - Congresses. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-69775-8
ISBN:	9783319697758

Towards integrative machine learning and knowledge extraction = BIRS Workshop, Banff, AB, Canada, July 24-26, 2015 : revised selected papers /
Towards integrative machine learning and knowledge extractionBIRS 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 ;10344..

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

Standard No.: 10.1007/978-3-319-69775-8doiSubjects--Topical Terms:

551626
Data mining
--Congresses.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

Towards integrative machine learning and knowledge extraction = BIRS Workshop, Banff, AB, Canada, July 24-26, 2015 : revised selected papers /
LDR:03284nmm a2200349 a 4500 001 2110816
003 DE-He213
005 20171028141530.0
006 m d
007 cr nn 008maaau
008 180619s2017 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 $a BIRS Workshop "Advances in Interactive Knowledge Discovery and Data Mining in Complex and Big Data Sets" $d (2015 : $c Banff, Alta.) $3 3264281
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 551626
650 0 $a Machine learning. $3 533906
650 0 $a Human-computer interaction $x Congresses. $3 705966
650 1 4 $a Computer Science. $3 626642
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 890894
650 2 4 $a Information Systems and Communication Service. $3 891044
650 2 4 $a Probability and Statistics in Computer Science. $3 891072
650 2 4 $a Software Engineering/Programming and Operating Systems. $3 891214
650 2 4 $a Computer Systems Organization and Communication Networks. $3 891212
700 1 $a Holzinger, Andreas. $3 1245649
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Lecture notes in computer science ; $v 10344. $3 3264282
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-69775-8
950 $a Computer Science (Springer-11645)