Data Mining by Evolving Agents for Clusters Discovery and Metric Learning

Neural Advances in Processing Nonlinear Dynamic Signals - Smart Innovation, Systems and Technologies ◽

10.1007/978-3-319-95098-3_3 ◽

2018 ◽

pp. 23-35

Author(s):

Alessio Martino ◽

Mauro Giampieri ◽

Massimiliano Luzi ◽

Antonello Rizzi

Keyword(s):

Data Mining ◽

Metric Learning

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An evolutionary agents based system for data mining and local metric learning

2018 IEEE International Conference on Industrial Technology (ICIT) ◽

10.1109/icit.2018.8352396 ◽

2018 ◽

Cited By ~ 3

Author(s):

Mauro Giampieri ◽

Antonello Rizzi

Keyword(s):

Data Mining ◽

Metric Learning

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Tree-Based Metric Learning for Distance Computation in Data Mining

Web Technologies and Applications - Lecture Notes in Computer Science ◽

10.1007/978-3-319-25255-1_31 ◽

2015 ◽

pp. 377-388

Author(s):

Ming Yan ◽

Yan Zhang ◽

Hongzhi Wang

Keyword(s):

Data Mining ◽

Metric Learning ◽

Distance Computation

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Survey on distance metric learning and dimensionality reduction in data mining

Data Mining and Knowledge Discovery ◽

10.1007/s10618-014-0356-z ◽

2014 ◽

Vol 29 (2) ◽

pp. 534-564 ◽

Cited By ~ 69

Author(s):

Fei Wang ◽

Jimeng Sun

Keyword(s):

Data Mining ◽

Dimensionality Reduction ◽

Metric Learning ◽

Distance Metric Learning ◽

Distance Metric

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Distance Metric Learning Approach for Weather Data Mining

Proceedings of the 2018 2nd International Conference on Big Data and Internet of Things - BDIOT 2018 ◽

10.1145/3289430.3289455 ◽

2018 ◽

Author(s):

Zhongfeng Niu ◽

Yian Zhu ◽

Linxiu Jiang

Keyword(s):

Data Mining ◽

Metric Learning ◽

Weather Data ◽

Learning Approach ◽

Distance Metric Learning ◽

Distance Metric

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Data Mining and Machine Learning

10.1017/9781108564175 ◽

2020 ◽

Cited By ~ 2

Author(s):

Mohammed J. Zaki ◽

Wagner Meira, Jr

Keyword(s):

Machine Learning ◽

Data Mining

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The economics of selection of mail orders Drs. Zahavi and Levin are the masterminds behind the development of AMOS, a customized predictive modeling system for the Franklin Mint in Philadelphia, and GainSmarts, a general purpose data mining system that is the two-time winner of the KDD-CUP competition for the best data mining tools (1997 and 1998) sponsored by the American Association for Artificial Intelligence.

Journal of Interactive Marketing ◽

10.1002/dir.1016.abs ◽

2001 ◽

Vol 15 (3) ◽

pp. 53

Author(s):

Nissan Levin ◽

Jacob Zahavi

Keyword(s):

Artificial Intelligence ◽

Data Mining ◽

Predictive Modeling ◽

American Association ◽

General Purpose ◽

Mining System ◽

Data Mining System ◽

Mining Tools ◽

Selection Of

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Heart Rate Variability, Emotions, and Music

Journal of Psychophysiology ◽

10.1027/0269-8803/a000021 ◽

2010 ◽

Vol 24 (2) ◽

pp. 112-119 ◽

Cited By ~ 9

Author(s):

F. Riganello ◽

A. Candelieri ◽

M. Quintieri ◽

G. Dolce

Keyword(s):

Data Mining ◽

Heart Rate ◽

Heart Rate Variability ◽

Vegetative State ◽

Low Frequency ◽

Emotional Reactions ◽

Heart Beat ◽

Healthy Controls ◽

Frequency Spectra ◽

Emotional Value

The purpose of the study was to identify significant changes in heart rate variability (an emerging descriptor of emotional conditions; HRV) concomitant to complex auditory stimuli with emotional value (music). In healthy controls, traumatic brain injured (TBI) patients, and subjects in the vegetative state (VS) the heart beat was continuously recorded while the subjects were passively listening to each of four music samples of different authorship. The heart rate (parametric and nonparametric) frequency spectra were computed and the spectra descriptors were processed by data-mining procedures. Data-mining sorted the nu_lf (normalized parameter unit of the spectrum low frequency range) as the significant descriptor by which the healthy controls, TBI patients, and VS subjects’ HRV responses to music could be clustered in classes matching those defined by the controls and TBI patients’ subjective reports. These findings promote the potential for HRV to reflect complex emotional stimuli and suggest that residual emotional reactions continue to occur in VS. HRV descriptors and data-mining appear applicable in brain function research in the absence of consciousness.

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