annotate tvii/logistic_regression.py @ 16:b95fe82ac9ce

more notes to self
author Jeff Hammel <k0scist@gmail.com>
date Sun, 03 Sep 2017 13:17:33 -0700
parents 8cb116d63a78
children 3713c6733990
Ignore whitespace changes - Everywhere: Within whitespace: At end of lines:
rev   line source
2
1214c127fe43 steps towards logistic regression
Jeff Hammel <k0scist@gmail.com>
parents:
diff changeset
1 """
1214c127fe43 steps towards logistic regression
Jeff Hammel <k0scist@gmail.com>
parents:
diff changeset
2 z = w'x + b
1214c127fe43 steps towards logistic regression
Jeff Hammel <k0scist@gmail.com>
parents:
diff changeset
3 a = sigmoid(z)
1214c127fe43 steps towards logistic regression
Jeff Hammel <k0scist@gmail.com>
parents:
diff changeset
4 L(a,y) = -(y*log(a) + (1-y)*log(1-a))
11
b6a146f0a61b [logistic regression] stubbing
Jeff Hammel <k0scist@gmail.com>
parents: 2
diff changeset
5
b6a146f0a61b [logistic regression] stubbing
Jeff Hammel <k0scist@gmail.com>
parents: 2
diff changeset
6 [| | | ]
b6a146f0a61b [logistic regression] stubbing
Jeff Hammel <k0scist@gmail.com>
parents: 2
diff changeset
7 X = [x1 x2 x3]
b6a146f0a61b [logistic regression] stubbing
Jeff Hammel <k0scist@gmail.com>
parents: 2
diff changeset
8 [| | | ]
b6a146f0a61b [logistic regression] stubbing
Jeff Hammel <k0scist@gmail.com>
parents: 2
diff changeset
9
b6a146f0a61b [logistic regression] stubbing
Jeff Hammel <k0scist@gmail.com>
parents: 2
diff changeset
10 [z1 z2 z3 .. zm] = w'*X + [b b b b ] = [w'*x1+b + w'*x2+b ...]
2
1214c127fe43 steps towards logistic regression
Jeff Hammel <k0scist@gmail.com>
parents:
diff changeset
11 """
11
b6a146f0a61b [logistic regression] stubbing
Jeff Hammel <k0scist@gmail.com>
parents: 2
diff changeset
12
b6a146f0a61b [logistic regression] stubbing
Jeff Hammel <k0scist@gmail.com>
parents: 2
diff changeset
13
b6a146f0a61b [logistic regression] stubbing
Jeff Hammel <k0scist@gmail.com>
parents: 2
diff changeset
14 import numpy as np
16
b95fe82ac9ce more notes to self
Jeff Hammel <k0scist@gmail.com>
parents: 13
diff changeset
15 from .sigmoid import sigmoid
b95fe82ac9ce more notes to self
Jeff Hammel <k0scist@gmail.com>
parents: 13
diff changeset
16
b95fe82ac9ce more notes to self
Jeff Hammel <k0scist@gmail.com>
parents: 13
diff changeset
17 def cost_function(_):
b95fe82ac9ce more notes to self
Jeff Hammel <k0scist@gmail.com>
parents: 13
diff changeset
18 """
b95fe82ac9ce more notes to self
Jeff Hammel <k0scist@gmail.com>
parents: 13
diff changeset
19 Cost function for binary classification
b95fe82ac9ce more notes to self
Jeff Hammel <k0scist@gmail.com>
parents: 13
diff changeset
20 yhat = sigmoid(W.T*x + b)
b95fe82ac9ce more notes to self
Jeff Hammel <k0scist@gmail.com>
parents: 13
diff changeset
21 interpret yhat thhe probably that y=1
b95fe82ac9ce more notes to self
Jeff Hammel <k0scist@gmail.com>
parents: 13
diff changeset
22
b95fe82ac9ce more notes to self
Jeff Hammel <k0scist@gmail.com>
parents: 13
diff changeset
23 Loss function:
b95fe82ac9ce more notes to self
Jeff Hammel <k0scist@gmail.com>
parents: 13
diff changeset
24 y log(yhat) + (1- {UNFINISHED})
b95fe82ac9ce more notes to self
Jeff Hammel <k0scist@gmail.com>
parents: 13
diff changeset
25 """
b95fe82ac9ce more notes to self
Jeff Hammel <k0scist@gmail.com>
parents: 13
diff changeset
26 raise NotImplementedError('TODO')
11
b6a146f0a61b [logistic regression] stubbing
Jeff Hammel <k0scist@gmail.com>
parents: 2
diff changeset
27
12
8d25213513b4 [regression] notes to self
Jeff Hammel <k0scist@gmail.com>
parents: 11
diff changeset
28 def logistic_regression(_):
8d25213513b4 [regression] notes to self
Jeff Hammel <k0scist@gmail.com>
parents: 11
diff changeset
29 """the slow way"""
13
8cb116d63a78 [notes]
Jeff Hammel <k0scist@gmail.com>
parents: 12
diff changeset
30 J = 0
8cb116d63a78 [notes]
Jeff Hammel <k0scist@gmail.com>
parents: 12
diff changeset
31 dw1 =0
8cb116d63a78 [notes]
Jeff Hammel <k0scist@gmail.com>
parents: 12
diff changeset
32 dw2=0
8cb116d63a78 [notes]
Jeff Hammel <k0scist@gmail.com>
parents: 12
diff changeset
33 db=0
12
8d25213513b4 [regression] notes to self
Jeff Hammel <k0scist@gmail.com>
parents: 11
diff changeset
34
11
b6a146f0a61b [logistic regression] stubbing
Jeff Hammel <k0scist@gmail.com>
parents: 2
diff changeset
35 def logistic_regression(nx):
b6a146f0a61b [logistic regression] stubbing
Jeff Hammel <k0scist@gmail.com>
parents: 2
diff changeset
36 dw = np.zeros(nx)
b6a146f0a61b [logistic regression] stubbing
Jeff Hammel <k0scist@gmail.com>
parents: 2
diff changeset
37 # TODO
b6a146f0a61b [logistic regression] stubbing
Jeff Hammel <k0scist@gmail.com>
parents: 2
diff changeset
38 # z = np.dot(wT, x) + b # "boradcasting
b6a146f0a61b [logistic regression] stubbing
Jeff Hammel <k0scist@gmail.com>
parents: 2
diff changeset
39 raise NotImplementedError('TODO')
b6a146f0a61b [logistic regression] stubbing
Jeff Hammel <k0scist@gmail.com>
parents: 2
diff changeset
40
b6a146f0a61b [logistic regression] stubbing
Jeff Hammel <k0scist@gmail.com>
parents: 2
diff changeset
41 # derivativs:
b6a146f0a61b [logistic regression] stubbing
Jeff Hammel <k0scist@gmail.com>
parents: 2
diff changeset
42 # dz1 = a1 - y1 ; dz2 = a2 - y2 ; ....
b6a146f0a61b [logistic regression] stubbing
Jeff Hammel <k0scist@gmail.com>
parents: 2
diff changeset
43 # dZ = [ dz1 dz2 ... dzm ]
12
8d25213513b4 [regression] notes to self
Jeff Hammel <k0scist@gmail.com>
parents: 11
diff changeset
44 # Z = w'X + b = np.dot(w', X) + b
8d25213513b4 [regression] notes to self
Jeff Hammel <k0scist@gmail.com>
parents: 11
diff changeset
45 # A sigmoid(Z)
8d25213513b4 [regression] notes to self
Jeff Hammel <k0scist@gmail.com>
parents: 11
diff changeset
46 #dZ = A - Y
8d25213513b4 [regression] notes to self
Jeff Hammel <k0scist@gmail.com>
parents: 11
diff changeset
47 #dw = (1./m)*X*dZ'
8d25213513b4 [regression] notes to self
Jeff Hammel <k0scist@gmail.com>
parents: 11
diff changeset
48 #db = (1./m)*np.sum(dZ)
8d25213513b4 [regression] notes to self
Jeff Hammel <k0scist@gmail.com>
parents: 11
diff changeset
49 # w -= alpha*dw
8d25213513b4 [regression] notes to self
Jeff Hammel <k0scist@gmail.com>
parents: 11
diff changeset
50 # b -= alpha*db