Notes in Machine Learning with Python(3)

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Environment Problem

• numpy and scipy
• normal ones:pip install pandas quandl sklearn numpy matplotlib
• pythonprogramming.net
• github

Kernels

change the linearly inseparable data into a linearly separable data

Why Kernels

K(x ,x') = z.z' //The Kernel function

z = function(x)
z' = function(x-)

X = [x1,x2] //simple dataset

// the kernel wants to be 2nd order polynomial

Z = [1,x1,x2,x1^2,x2^2,x1x2]

Z' = [1,x1',x2',x1'^2,x2'^2,x1'x2']

K(x ,x') = Z.Z' = 1+x1x1'+ ... +x1x2x1'x2'

K(x, x') = (1 + x1x1' + ... + xnxn')^p // polynomial Kernel

p: order of polynomial
n: dimensions

// Learn more about Exponential kernel for RBF

Soft Margin SVM

google: svm kernel visualization overlapping —> softmax polynomial kernel

SVM Parameters

multi-classes

• OVR : one vs rest
• OVO : one vs one
• sklearn.svm.svc
• decision_function_shape(default = ‘ovr’)