Journal ArticleDOI
Pattern Recognition and Machine Learning
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TLDR
This book covers a broad range of topics for regular factorial designs and presents all of the material in very mathematical fashion and will surely become an invaluable resource for researchers and graduate students doing research in the design of factorial experiments.Abstract:
(2007). Pattern Recognition and Machine Learning. Technometrics: Vol. 49, No. 3, pp. 366-366.read more
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Time Series FeatuRe Extraction on basis of Scalable Hypothesis tests (tsfresh – A Python package)
TL;DR: The Python package tsfresh (Time Series FeatuRe Extraction on basis of Scalable Hypothesis tests) accelerates this process by combining 63 time series characterization methods, which by default compute a total of 794 time series features, with feature selection on basis automatically configured hypothesis tests.
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Mining data with random forests: A survey and results of new tests
TL;DR: Random forests has become a popular technique for classification, prediction, studying variable importance, variable selection, and outlier detection, and results of new tests regarding variable rankings based on RF variable importance measures are presented.
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Estimating the age of healthy subjects from T1-weighted MRI scans using kernel methods: exploring the influence of various parameters
TL;DR: A framework for automatically and efficiently estimating the age of healthy subjects from their T(1)-weighted MRI scans using a kernel method for regression is introduced and indicated favorable performance of the RVM and identified the number of training samples as the critical factor for prediction accuracy.
Proceedings ArticleDOI
Health Monitoring and Management Using Internet-of-Things (IoT) Sensing with Cloud-Based Processing: Opportunities and Challenges
Moeen Hassanalieragh,Alex Page,Tolga Soyata,Gaurav Sharma,Mehmet K. Aktas,Gonzalo Mateos,Burak Kantarci,Silvana Andreescu +7 more
TL;DR: The availability of data at hitherto unimagined scales and temporal longitudes coupled with a new generation of intelligent processing algorithms can facilitate an evolution in the practice of medicine and help reduce the cost of health care while simultaneously improving outcomes.
Journal ArticleDOI
Dirichlet Multinomial Mixtures: Generative Models for Microbial Metagenomics
TL;DR: It is proposed that obesity is not associated with a distinct microbiota but increases the chance that an individual derives from a disturbed enterotype, an example of the ‘Anna Karenina principle (AKP)’ applied to microbial communities.