8. Game of Life Wikipedia (2006). Image:Gospers glider gun.gif - Wikipedia, the free encyclopedia. http://en.wikipedia.org/wiki/Image:Gospers_glider_gun.gif . [Accessed 16-10-06].
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11. Randomly Ordered Data Don’t Sell Yes Cold Overcast Don’t Sell No Cold Sunny Don’t Sell No Hot Overcast Sell No Hot Sunny Sell Yes Mild Sunny Don’t Sell Yes Mild Overcast Result Holiday Season Temperature Outlook
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16. Example 1 Root node Branch Leaf Node Outlook Temperature Sunny Hot Sell Don’t Sell Sell Yes No Mild Holiday Season Cold Don’t Sell Holiday Season Overcast No Don’t Sell Yes Temperature Hot Cold Mild Don’t Sell Sell Don’t Sell
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18. Ambiguous Trees Consider the following data: - True False 3 - True True 4 2 1 Item + False True + False False Class Y X
37. Final Tree Transport {7,12,16,19,20} Positive {8} Negative {6} Negative Callan 2003:243 {5,9,14} P ositive {2,4,10,13,18} Negative A P G {1,3,6,8,11,15,17} Housing Estate L M S N {11,17} Industrial Estate {17} Negative {11} P ositive Y N {1,3,15} University {15} Negative {1,3} P ositive Y N {2,4,5,9,10,13,14,18} Industrial Estate Y N
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41. Rules Example Transport {1,3,6,8,11,15,17} Housing Estate {2,4,5,9,10,13,14,18} Industrial Estate {7,12,16,19,20} Positive {11,17} Industrial Estate {1,3,15} University {8} Negative {6} Negative {5,9,14} P ositive {2,4,10,13,18} Negative {17} Negative {11} P ositive {15} Negative {1,3} P ositive A P G L M S N Y N Y N Callan 2003:243 Y N
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Editor's Notes
See also Hastie, T., Tibshirani, R. & Friedman, J.H. (2001). The Elements of Statistical Learning: Data Mining, Inference, and Prediction . New York: Springer-Verlag: Least squares: linear model, given a set of points, attempt to fit a line/boundary by minimising the residual sum of squares. Decision trees: our focus. Support vector machines: non-linear boundaries represented as linear boundaries in transformed (high-dimensional) space. Boosting: combine weak classifiers and tune the training data. Neural networks: biologically inspired supervised and unsupervised techniques. K-means: given a set of points, attempt to fit k-nearest neighbours to the points. Genetic algorithms: evolutionary techniques to evolve solutions using a fitness function/breeding/mutation. Neuron image: http://cwabacon.pearsoned.com/bookbind/pubbooks/pinel_ab/chapter3/deluxe.html. Genetic video: http://www.naturalmotion.com/files/simplewalkevolution.mpg.
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