Chapter 8: Distance Based Models

flach_ch_8

# Chapter 8: Distance Based Models

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# K Nearest Neighbors

Time to train: O(N)

Time to classify: O(N)

The curse of dimensionality!

Python Implementation: http://machinelearningmastery.com/tutorial-to-implement-k-nearest-neighbors-in-python-from-scratch/

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# K Means

NP-Complete Clustering Algorithm

Two Biggest Issues:

1. Are the convergence points accurate?
2. What should K be?

Great Links

1. http://www.onmyphd.com/?p=k-means.clustering
2. http://en.wikipedia.org/wiki/Determining_the_number_of_clusters_in_a_data_set
3. http://papers.nips.cc/paper/2526-learning-the-k-in-k-means.pdf

Other Links

1. https://datasciencelab.wordpress.com/2013/12/12/clustering-with-k-means-in-python/
2. http://stackoverflow.com/questions/9847026/plotting-output-of-kmeanspycluster-impl
3. https://spark-summit.org/2013/exercises/machine-learning-with-spark.html

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# Hierarchical Clustering

Dendrogram
Simple/Complete/Average/Centroid Linkage

Links

1. http://stackoverflow.com/questions/11917779/how-to-plot-and-annotate-hierarchical-clustering-dendrograms-in-scipy-matplotlib
2 (?). http://brandonrose.org/clustering

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# Kernels

WTF

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