Machine Learning/Datasets

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This page describes in detail the datasets used for the [[NBML Course]].
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Machine learning is a vast field and there are many different types of problems to be solved. If you find a dataset interesting, try to categorize it (or add a new category) and add it to the links below.
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===Classification===
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*[http://yann.lecun.com/exdb/mnist/ MNIST Handwritten Digits]
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**Classify handwritten digits using this dataset, a very popular one with lots of training examples.
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*[http://archive.ics.uci.edu/ml/datasets/Heart+Disease Heart Disease]
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**Predict whether a person will have heart disease based on a subset of 76 factors.
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*[http://archive.ics.uci.edu/ml/datasets/Census-Income+%28KDD%29 Census Income]
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**Try to predict whether a person has an income greater than or less than 50k
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===Regression===
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*[http://www.sci.usq.edu.au/staff/dunn/Datasets/Books/Hand/Hand-R/alps-R.html Boiling point in the Alps]
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**The boiling point of water at different barometric pressures.
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*[http://www.sci.usq.edu.au/staff/dunn/Datasets/Books/Hand/Hand-R/shocking-R.html Shocking Rats]
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**How does shocking a rat affect it's ability to complete a maze?
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*[http://www.sci.usq.edu.au/staff/dunn/Datasets/Books/Hand/Hand-R/icecream-R.html Ice Cream Sales]
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**Predict the quantity of ice cream consumed based on some other variables.
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*[http://www.sci.usq.edu.au/staff/dunn/Datasets/applications/health/fev.html Smoking and Respiratory Function]
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**How does smoking affect lung capacity?
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===Time Series===
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*[http://robjhyndman.com/tsdldata/data/ausgundeaths.dat Gun-related Deaths in Australia]
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**"Deaths from gun-related homicides and suicides and non-gun-related homicides and suicides. Australia: 1915-2004. Source: Neill and Leigh (2007)."
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*[http://robjhyndman.com/tsdldata/data/immig.dat Immigration Rates]
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**"Annual immigration into the United States: thousands. 1820 – 1962. From Kendall & Ord (1990), p.13."
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*[http://robjhyndman.com/tsdldata/roberts/beards.dat Percent of Men with Beards 1866-1911]
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**"Percent of Men with full beards, 1866 – 1911. Source: Hipel and Mcleod (1994)."
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*[http://robjhyndman.com/tsdldata/roberts/velmon.dat Velocity of Money in America 1869-1960]
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**The [http://en.wikipedia.org/wiki/Velocity_of_money velocity of money] is basically the number of times a single unit of money changes hands over a period of time.  Theory goes, MV=PY, or Velocity = Prices * Economic Output / Quantity of Money.
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*[http://robjhyndman.com/tsdldata/annual/globtp.dat Changes in Global Air Temperature 1880-1985]
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**"Surface air temperature change for the globe, 1880-1985, Temperature change actually means temperature against an arbitrary zero point. From James Hansen and Sergej Lebedeff, "Global Trends of Measured Surface Air Temperature", `Journal of Geophysical Research`, Vol. 92, No. D11, pages 13,345-13,372, November 20, 1987."
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*[http://robjhyndman.com/tsdldata/data/earthq.dat Number of Earthquakes per Year 1900-1988 (>= 7.0)]
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**"Source: National Earthquake Information Center. Different lists will give different numbers depending on the formula used for calculating the magnitude."
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===Clustering===
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*[http://archive.ics.uci.edu/ml/datasets/Plants USDA Plants Data]
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**Automatically cluster plants based on 70 attributes.
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*[http://www.uni-koeln.de/themen/statistik/data/cluster/ Nutriens in Meat, Fish and Fowl]
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**Can you cluster into animal type given the data?
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===Text Data===
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*[http://www.cs.cmu.edu/~enron/ Enron Emails]
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**Search through Enron's publicly accessible emails.
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*[http://archive.ics.uci.edu/ml/datasets/Bag+of+Words Bag of Words]
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**Collection of word counts for various types of documents, including Enron emails, scientific papers, and New York Times articles.
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===Reinforcement Learning===

Latest revision as of 23:07, 15 March 2011

Machine learning is a vast field and there are many different types of problems to be solved. If you find a dataset interesting, try to categorize it (or add a new category) and add it to the links below.

Contents

[edit] Classification

  • MNIST Handwritten Digits
    • Classify handwritten digits using this dataset, a very popular one with lots of training examples.
  • Heart Disease
    • Predict whether a person will have heart disease based on a subset of 76 factors.
  • Census Income
    • Try to predict whether a person has an income greater than or less than 50k

[edit] Regression

[edit] Time Series

  • Gun-related Deaths in Australia
    • "Deaths from gun-related homicides and suicides and non-gun-related homicides and suicides. Australia: 1915-2004. Source: Neill and Leigh (2007)."
  • Immigration Rates
    • "Annual immigration into the United States: thousands. 1820 – 1962. From Kendall & Ord (1990), p.13."
  • Percent of Men with Beards 1866-1911
    • "Percent of Men with full beards, 1866 – 1911. Source: Hipel and Mcleod (1994)."
  • Velocity of Money in America 1869-1960
    • The velocity of money is basically the number of times a single unit of money changes hands over a period of time. Theory goes, MV=PY, or Velocity = Prices * Economic Output / Quantity of Money.
  • Changes in Global Air Temperature 1880-1985
    • "Surface air temperature change for the globe, 1880-1985, Temperature change actually means temperature against an arbitrary zero point. From James Hansen and Sergej Lebedeff, "Global Trends of Measured Surface Air Temperature", `Journal of Geophysical Research`, Vol. 92, No. D11, pages 13,345-13,372, November 20, 1987."
  • Number of Earthquakes per Year 1900-1988 (>= 7.0)
    • "Source: National Earthquake Information Center. Different lists will give different numbers depending on the formula used for calculating the magnitude."

[edit] Clustering

[edit] Text Data

  • Enron Emails
    • Search through Enron's publicly accessible emails.
  • Bag of Words
    • Collection of word counts for various types of documents, including Enron emails, scientific papers, and New York Times articles.


[edit] Reinforcement Learning

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