weka.classifiers.functions.Winnow 屬錯誤驅動型學習器，
只處理文字屬性，將之轉成二元屬性，用來預測二元類別值。可線上累進學習。
適用在案例集屬性眾多，卻多數和預測不相關情況，可以快速鎖定相關屬性作預測。
給定案例屬性(a0, a1, ..., ak)，門檻 theta，權重升級係數alpha，權重降級係數beta，
權重向量(w0, w1, ..., wk)或(w0+ - w0-, w1+ - w1-, ..., wk+ - wk-)
其中，所有符號皆為正數，擴充屬性 a0 恆為 1。則預測式有二:
不平衡版: 權重向量各維度只能正數
w0 * a0 + w1 * a1 + ... + wk * ak > theta 表類別1; 否則類別2
平衡版: 權重向量各維度允許負數
(w0+ - w0-) * a0 + (w1+ - w1-) * a1 + ... + (wk+ - wk-) * ak > theta 表類別1; 否則類別2
學習過程若遇預測錯誤，則權重向量調整法如下:
類別2誤為類別1: w *= beta 或 w+ *= beta and w- *= alpha 讓權重變小
類別1誤為類別2: w *= alpha 或 w+ *= alpha and w- *= beta 讓權重變大
參數說明:
-L 使用平衡版。預設值false
-I 套用訓練集學習權重的輪數。預設值1
-A 權重升級係數alpha，需>1。預設值2.0
-B 權重降級係數beta，需<1。預設值0.5
-H 預測門檻theta。預設值-1，表示屬性個數
-W 權重初始值，需>0。預設值2.0
-S 亂數種子，影響訓練集的案例訓練順序。預設值1
> java weka.classifiers.functions.Winnow -t data\weather.nominal.arff
Winnow
Attribute weights
w0 8.0
w1 1.0
w2 2.0
w3 4.0
w4 2.0
w5 2.0
w6 1.0
w7 1.0
Cumulated mistake count: 7
Time taken to build model: 0 seconds
Time taken to test model on training data: 0 seconds
=== Error on training data ===
Correctly Classified Instances 10 71.4286 %
Incorrectly Classified Instances 4 28.5714 %
Kappa statistic 0.3778
Mean absolute error 0.2857
Root mean squared error 0.5345
Relative absolute error 61.5385 %
Root relative squared error 111.4773 %
Total Number of Instances 14
=== Confusion Matrix ===
a b <-- classified as
7 2 | a = yes
2 3 | b = no
=== Stratified cross-validation ===
Correctly Classified Instances 7 50 %
Incorrectly Classified Instances 7 50 %
Kappa statistic -0.2564
Mean absolute error 0.5
Root mean squared error 0.7071
Relative absolute error 105 %
Root relative squared error 143.3236 %
Total Number of Instances 14
=== Confusion Matrix ===
a b <-- classified as
7 2 | a = yes
5 0 | b = no
如下 weather.nominal.arff 案例集的14個案例利用4個文字屬性，預測文字屬性。
| outlook |
temperature |
humidity |
windy |
play |
| sunny |
hot |
high |
FALSE |
no |
| sunny |
hot |
high |
TRUE |
no |
| overcast |
hot |
high |
FALSE |
yes |
| rainy |
mild |
high |
FALSE |
yes |
| rainy |
cool |
normal |
FALSE |
yes |
| rainy |
cool |
normal |
TRUE |
no |
| overcast |
cool |
normal |
TRUE |
yes |
| sunny |
mild |
high |
FALSE |
no |
| sunny |
cool |
normal |
FALSE |
yes |
| rainy |
mild |
normal |
FALSE |
yes |
| sunny |
mild |
normal |
TRUE |
yes |
| overcast |
mild |
high |
TRUE |
yes |
| overcast |
hot |
normal |
FALSE |
yes |
| rainy |
mild |
high |
TRUE |
no |
|
參考:
1.weka.classifiers.functions.Winnow
code | doc
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