Stanford ml neuralnetwork

11
Stanford ML Lecture #8 Neural Network Representation S. Takei @shtaag 2012年1月26日木曜日

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Explanation for Stanford Online Machine Learning class, chapter 8 neural network

Transcript of Stanford ml neuralnetwork

Page 1: Stanford ml neuralnetwork

Stanford ML Lecture #8 Neural NetworkRepresentationS. Takei @shtaag

2012年1月26日木曜日

Page 2: Stanford ml neuralnetwork

Reference

Stanford Online ML class #8

”Machine Learning: An Algorithmic Perspective” (Marsland, 2009)

2012年1月26日木曜日

http://www.ml-class.org/course/auth/index
http://www.ml-class.org/course/auth/index
http://amzn.to/zC4Szd
http://amzn.to/zC4Szd
http://amzn.to/zC4Szd
http://amzn.to/zC4Szd
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Why NN is necessary?

in non-linear classification problem...

polynomial regression is not efficient!!

ex. 50 x 50 pixels picture

n features = 2500

quadratic features = 50C2 = 3000000

O(Tn2) : where T = iterations

2012年1月26日木曜日

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Neuron Model

logistic activation function

O(T m n) : where m = input n = output T = iterations

more efficient than polynomial regression!!

2012年1月26日木曜日

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Simple Type : PERCEPTRON

1 layer of Input nodes

1 layer of Output nodes

weighted connections

only forward propagation

learning :

update weights based on error function

error function = difference between output values

2012年1月26日木曜日

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Represents logical operation

AND

Input1 Input2 out

0 0 0

0 1 0

1 0 0

1 1 1In1

In2

linear boundary

2012年1月26日木曜日

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Represents logical operation

OR

Input1 Input2 out

0 0 0

0 1 1

1 0 1

1 1 1In1

In2

linear boundary

2012年1月26日木曜日

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Represents logical operation

XOR

Input1 Input2 out

0 0 0

0 1 1

1 0 1

1 1 0In1

In2

Can’t separate linearly!!

?

2012年1月26日木曜日

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Perceptron (2D) can’t represent XOR( Minsky & Papert, “Perceptrons”, 1969)

1, add dimension -> Support Vector Machine

2, add layers -> Neural Network

2012年1月26日木曜日

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Neural Network

Input layers + output layers + hidden layers

learning :

backward propagation

2012年1月26日木曜日

Page 11: Stanford ml neuralnetwork

Neural Network can represent XOR

XOR = (In1 AND In2) OR (In1 NAND In2)

2012年1月26日木曜日


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