featureselectsequential01.txt

来自「这是台湾张智星的模式识别的课件的源码」· 文本 代码 · 共 28 行

Construct 10 KNN models, each with up to 4 inputs selected from 4 candidates...

Selecting input 1:
Model 1/10:sepal length --> Recognition rate = 58.7%
Model 2/10:sepal width --> Recognition rate = 48.0%
Model 3/10:petal length --> Recognition rate = 88.0%
Model 4/10:petal width --> Recognition rate = 88.0%
Currently selected inputs: petal length

Selecting input 2:
Model 5/10:petal length, sepal length --> Recognition rate = 90.7%
Model 6/10:petal length, sepal width --> Recognition rate = 90.7%
Model 7/10:petal length, petal width --> Recognition rate = 95.3%
Currently selected inputs: petal length, petal width

Selecting input 3:
Model 8/10:petal length, petal width, sepal length --> Recognition rate = 95.3%
Model 9/10:petal length, petal width, sepal width --> Recognition rate = 95.3%
Currently selected inputs: petal length, petal width, sepal length

Selecting input 4:
Model 10/10:petal length, petal width, sepal length, sepal width --> Recognition rate = 96.0%
Currently selected inputs: petal length, petal width, sepal length, sepal width

Overall maximal recognition rate = 96.0%.
Overall selected inputs: petal length, petal width, sepal length, sepal width