Dawn E. Holmes

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Dawn E. Holmes



Average rating: 3.67 · 264 ratings · 23 reviews · 21 distinct worksSimilar authors
Big Data: A Very Short Intr...

3.66 avg rating — 249 ratings — published 2018 — 6 editions
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Innovations in Bayesian Net...

really liked it 4.00 avg rating — 3 ratings — published 2008 — 6 editions
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Data Mining: Foundations an...

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4.50 avg rating — 2 ratings — published 2011 — 3 editions
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Innovations in Machine Lear...

liked it 3.00 avg rating — 3 ratings — published 2006 — 3 editions
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Advances in Biomedical Info...

3.50 avg rating — 2 ratings5 editions
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Data Mining: Foundations an...

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it was amazing 5.00 avg rating — 1 rating — published 2011 — 2 editions
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Data Mining: Foundations an...

it was amazing 5.00 avg rating — 1 rating — published 2012
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Stat Class

really liked it 4.00 avg rating — 1 rating5 editions
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Data Mining: Foundations an...

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really liked it 4.00 avg rating — 1 rating — published 2012 — 4 editions
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Data Mining: Foundations an...

really liked it 4.00 avg rating — 1 rating — published 2012 — 2 editions
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“Search engine query data is not the product of a designed statistical experiment and finding a way to meaningfully analyse such data and extract useful knowledge is a new and challenging field that would benefit from collaboration. For the 2012–13 flu season, Google made significant changes to its algorithms and started to use a relatively new mathematical technique called Elasticnet, which provides a rigorous means of selecting and reducing the number of predictors required. In 2011, Google launched a similar program for tracking Dengue fever, but they are no longer publishing predictions and, in 2015, Google Flu Trends was withdrawn. They are, however, now sharing their data with academic researchers...

Google Flu Trends, one of the earlier attempts at using big data for epidemic prediction, provided useful insights to researchers who came after them...

The Delphi Research Group at Carnegie Mellon University won the CDC’s challenge to ‘Predict the Flu’ in both 2014–15 and 2015–16 for the most accurate forecasters. The group successfully used data from Google, Twitter, and Wikipedia for monitoring flu outbreaks.”
Dawn E. Holmes, Big Data: A Very Short Introduction



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