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Towards integrative machine learning...

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

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

Record Type:	Electronic resources : Monograph/item
Title/Author:	Towards integrative machine learning and knowledge extraction/ edited by Andreas Holzinger ... [et al.].
Reminder of title:	BIRS Workshop, Banff, AB, Canada, July 24-26, 2015 : revised selected papers /
remainder title:	BIRS Workshop
other author:	Holzinger, Andreas.
corporate name:	BIRS Workshop "Advances in Interactive Knowledge Discovery and Data Mining in Complex and Big Data Sets"
Published:	Cham :Springer International Publishing : : 2017.,
Description:	xvi, 207 p. :ill., digital ;24 cm.
[NT 15003449]:	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
Subject:	Data mining - Congresses. -
Online resource:	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 /
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