Machine Learning/Datasets

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*[http://robjhyndman.com/tsdldata/roberts/beards.dat Percent of Men with Beards 1866-1911]
 
*[http://robjhyndman.com/tsdldata/roberts/beards.dat Percent of Men with Beards 1866-1911]
 
**"Percent of Men with full beards, 1866 – 1911. Source: Hipel and Mcleod (1994)."
 
**"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 amount of money that changes hands over a year.
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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
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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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===Clustering===
 
===Clustering===

Revision as of 23:55, 14 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

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

Regression

Time Series

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."


Clustering

Personal tools