ML.KNN.DistFunctions

Package ML :: Package KNN :: Module DistFunctions |
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# Module DistFunctions

source code

Functions | [hide private]
EuclideanDist(ex1, ex2, attrs) >>> v1 = [0,1,0,1]... | source code
TanimotoDist(ex1, ex2, attrs) >>> v1 = [0,1,0,1]... | source code
_test() | source code

Function Details | [hide private]

### EuclideanDist(ex1, ex2, attrs) | source code
    >>> v1 = [0,1,0,1]
    >>> v2 = [1,0,1,0]
    >>> EuclideanDist(v1,v2,range(4))
    2.0
    >>> EuclideanDist(v1,v1,range(4))
    0.0
    >>> v2 = [0,0,0,1]
    >>> EuclideanDist(v1,v2,range(4))
    1.0
    >>> v2 = [0,.5,0,.5]
    >>> abs(EuclideanDist(v1,v2,range(4))-1./math.sqrt(2))<1e-4
    1

### TanimotoDist(ex1, ex2, attrs) | source code
    >>> v1 = [0,1,0,1]
    >>> v2 = [1,0,1,0]
    >>> TanimotoDist(v1,v2,range(4))
    1.0
    >>> v2 = [1,0,1,1]
    >>> TanimotoDist(v1,v2,range(4))
    0.75
    >>> TanimotoDist(v2,v2,range(4))
    0.0

    # this tests Issue 122
    >>> v3 = [0,0,0,0]
    >>> TanimotoDist(v3,v3,range(4))
    1.0