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Search results “Dimensionally modeled data mining”
Multi Dimensional Data Model
 
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Chawan Barzan UHD - Computer Science 4th Stage 2016-2017
Views: 4930 Chawan Barzan
Reducing High Dimensional Data with PCA and prcomp: ML with R
 
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This has been re-designed as 'Reducing High Dimensional Data in R' on Udemy.com, $19 COUPON!!!: https://www.udemy.com/practical-data-science-reducing-high-dimensional-data-in-r/?couponCode=1111 Check out my other in-depth classes on Udemy.com (discounts and specials) at http://amunategui.github.io/udemy/ In this R video, we'll see how PCA can reduce a 1000+ variable data set into 10 variables and barely lose accuracy! Walkthrough & code: http://amunategui.github.io/high-demensions-pca/ Note: data source url in the video no longer works, see the walkthrough for new source: http://amunategui.github.io/high-demensions-pca/ Note: for those that can't use xgboost - I added an alternative script using GBM in the walkthrough: http://amunategui.github.io/high-demensions-pca/ Top of the page under resources look for link: "Alternative GBM Source Code - for those that can't use xgboost" Machine Learning with R. If you liked this video - give me a thumbs up! Thx
Views: 38232 Manuel Amunategui
Brendan Herger | Machine Learning Techniques for Class Imbalances & Adversaries
 
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PyData DC 2016 There are many areas of applied Machine Learning which require models optimized for rare occurrences (i.e. class imbalance), as well as users actively attempting to subvert the system (i.e. adversaries). This talk will guide the audience through multiple published techniques which specifically attempt to address these issues. The Data Innovation Lab at Capital One has explored more advanced modeling techniques for class imbalance & adversarial actors. Our use case has allowed us to survey the many related fields which deal with these issues, and attempt many of the suggested modeling techniques. Additionally, we have introduce a few novel variations of our own. This talk will provide an introduction to the problem space, a brief overview of the modeling frameworks we've chosen to work with, a brief overview of our approaches, a discussion of lessons learned, and our proposed future work. The approaches discussed will include ensemble models, deep learning, genetic algorithms, outlier detection via dimensionally reduction (PCA and neural network auto-encoders), time-decay weighting, and Synthetic Minority Over-sampling Technique (SMOTE sampling).
Views: 3119 PyData
Lec-33 Dimensionality reduction Using PCA
 
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Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics and Electrical Communication Engineering, IIT Kharagpur. For more details on NPTEL visit http://nptel.iitm.ac.in
Views: 28385 nptelhrd
Sparse Grid Surrogate Model for the Elongated Lid-Driven Cavity
 
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Sparse Grid Surrogate Model for the Elongated Lid-Driven Cavity with Three Parameters
Views: 151 Daniel Butnaru
DEC 94: Telecollaborative Data Exploration
 
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DEC-CRL 94: Tools to register and segment soft tissue from medical images and visualize it three-dimensionally. Numerous techniques have been developed for biomedical image segmentation, but most methods do not perform well on a broad variety of data. We present an interactive approach to the segmentation of medical images. This approach is based on interactive deformable contours and has broad applicability to soft tissue segmentation. We describe a system, implemented in AVS, that we have applied to the segmentation of nerve cells and a human embryo heart from serial tissue sections, and the segmentation of lymph nodes from CT data. This work was conducted in the Visualization Group of the Cambridge Research Lab of Digital Equipment Corporation (Cambridge, MA). In collaboration with Dr. Ingrid Carlbom, William Hsu and Dr. Demetri Terzopoulos. Thyroid data courtesy of Dr. Michael Doyle from UCSF. Neuron data courtesy of Dr. Kristen Harris from Children's Hospital, Boston. Special thanks to Maria Loughlin and Dr. Keith Waters for video production assistance. See also: http://campar.in.tum.de/Chair/KlinkerCRL http://ar.in.tum.de/Chair/PublicationDetail?pub=klinker1994TR94-6 http://ar.in.tum.de/Chair/PublicationDetail?pub=klinker1995cvrmed
Webinar: Analyzing and Using RDoC Data in Your Research
 
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On May 10, 2016, the NIMH Research Domain Criteria (RDoC) Unit hosted a webinar featuring three NIMH-funded researchers discussing how to analyze and integrate RDoC data. They offer varied perspectives on how to incorporate RDoC principles in research. Presenters: Lisa McTeague, Ph.D. Dr. McTeague is a clinical psychologist and an assistant professor in the Brain Stimulation Laboratory of the Department of Psychiatry and Behavioral Sciences at the Medical University of South Carolina (MUSC). She is working to develop neurocircuit-informed treatment adjuncts for cognitive-behavioral approaches for PTSD, targeting deficits demonstrated in experimental affective neuroscience. Aristotle Voineskos, M.D., Ph.D. Dr. Voineskos is an associate professor in the Department of Psychiatry, Faculty of Medicine at the University of Toronto. Dr. Voineskos’ work combines multi-modal neuroimaging and genetics approaches to map gene effects in the brain with a view to discovering vulnerability pathways for severe mental illness. Meredith Wallace, Ph.D. Dr. Wallace is an assistant professor in the Department of Psychiatry at the University of Pittsburgh. Dr. Wallace is currently the principal investigator of a federally-funded career development award concentrating on statistical methods for developing RDoC-based multidimensional profiles. For More information, see: http://www.nimh.nih.gov/news/science-news/2016/webinar-analyzing-and-using-rdoc-data-in-your-research.shtml
2011 Frontiers of Engineering: Additive Manufacturing is Changing Surgery
 
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National Academy of Engineering 2011 U.S. Frontiers of Engineering Symposium September 19-21, 2011 Google, Inc. Mountain View, California Additive Manufacturing is Changing Surgery September 19, 2011 Presented by Andrew Christensen. ABSTRACT: Google hosted 100 attendees of the 2011 Nat'l Academy of Engineering's U.S. Frontiers of Engineering symposium (FOE) at our Mountain View office and Dinah's Garden Hotel in Palo Alto. The symposium is an annual three-day meeting that brings together 100 of the nation's outstanding young engineers (ages 30-45) from industry, academia, and government to discuss pioneering technical and leading-edge research in various engineering fields and industry sectors. About the speaker: Andrew Christensen is the President of Medical Modeling Inc. in Colorado.
Views: 3320 GoogleTechTalks
Toward data driven ontologies for mental function
 
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Event Date: August 20, 2018 Presenter: Russell A. Poldrack, Ph.D. The National Institutes of Health (NIH) Office of Behavioral and Social Science Research (OBSSR) hosts the 2017-2018 OBSSR Director’s Webinar Series. Abstract Psychological science has long been focused on the discovery of novel behavioral phenomena and the mechanistic explanation of those phenomena, which has led to a lack of cumulative conceptual progress. Dr. Poldrack will argue that the development of ontologies is essential for progress, but that these need to be tied directly to empirical data. He will provide an example from the domain of self-regulation, where we have used data-driven ontology development to describe the psychological structure of this domain and characterize its predictive validity with respect to real-world outcomes. Biography Russell A. Poldrack, Ph.D. Albert Ray Lang Professor of Psychology Professor (by courtesy) of Computer Science Stanford University Russell A. Poldrack is the Albert Ray Lang Professor in the Department of Psychology and Professor (by courtesy) of Computer Science at Stanford University, and Director of the Stanford Center for Reproducible Neuroscience. His research uses neuroimaging to understand the brain systems underlying decision making and executive function. His lab is also engaged in the development of neuroinformatics tools to help improve the reproducibility and transparency of neuroscience, including the Openneuro.org and Neurovault.org data sharing projects and the Cognitive Atlas ontology.
Kara Miller, Nigel Jacob, Kent Larson: "Innovative Cities" | Talks at Google
 
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In the third Thought Leaders at Google in Cambridge program, Kara Miller, host and executive editor of WGBH's Innovation Hub radio show discusses innovative cities with Nigel Jacob (Boston Mayor's Office for New Urban Mechanics) and Kent Larson (director of the MIT Media Lab’s Changing Places group).
Views: 1345 Talks at Google
A Comprehensive Review of Stability Analysis of Continuous Time Recurrent Neural Networks
 
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Views: 133 Ecway Karur