Machine Learning/Datasets: Difference between revisions
Jump to navigation
Jump to search
Mschachter (talk | contribs) mNo edit summary |
Mschachter (talk | contribs) mNo edit summary |
||
Line 1: | Line 1: | ||
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. | |||
===Classification=== | |||
*[http://yann.lecun.com/exdb/mnist/ MNIST Handwritten Digits] | *[http://yann.lecun.com/exdb/mnist/ MNIST Handwritten Digits] | ||
**Classify handwritten digits using this dataset, a very popular one with lots of training examples. | **Classify handwritten digits using this dataset, a very popular one with lots of training examples. | ||
Line 9: | Line 9: | ||
**Try to predict whether a person has an income greater than or less than 50k | **Try to predict whether a person has an income greater than or less than 50k | ||
===Regression=== | |||
*[http://www.sci.usq.edu.au/staff/dunn/Datasets/Books/Hand/Hand-R/alps-R.html Boiling point in the Alps] | *[http://www.sci.usq.edu.au/staff/dunn/Datasets/Books/Hand/Hand-R/alps-R.html Boiling point in the Alps] | ||
**The boiling point of water at different barometric pressures. | **The boiling point of water at different barometric pressures. | ||
Line 19: | Line 19: | ||
**How does smoking affect lung capacity? | **How does smoking affect lung capacity? | ||
===Time Series=== | |||
*[http://robjhyndman.com/tsdldata/data/ausgundeaths.dat Gun-related Deaths in Australia] | *[http://robjhyndman.com/tsdldata/data/ausgundeaths.dat 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)." | **"Deaths from gun-related homicides and suicides and non-gun-related homicides and suicides. Australia: 1915-2004. Source: Neill and Leigh (2007)." | ||
Line 27: | Line 27: | ||
**"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)." | ||
===Clustering=== |
Revision as of 23:44, 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.
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
- Boiling point in the Alps
- The boiling point of water at different barometric pressures.
- Shocking Rats
- How does shocking a rat affect it's ability to complete a maze?
- Ice Cream Sales
- Predict the quantity of ice cream consumed based on some other variables.
- Smoking and Respiratory Function
- How does smoking affect lung capacity?
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)."