Spis treści
Dane Grid8x8 - Wizualizacja QCP - Jedna klasa vs. reszta
Klasa 1
Klasa 2
Klasa 3
Klasa 4
Klasa 5
Dane Grid8x8 - Wizualizacja QCP - Jedna klasa vs. reszta
Klasa 1
G(x)= σ(x+β)(1-σ(x-β))
β=0.3
learningRate = 0.1
maxIterations = 1000
initiations = 10
eps = 0.001
lambda = 1.0
Klasa 2
G(x)= σ(x+β)(1-σ(x-β))
β=0.3
learningRate = 0.1
maxIterations = 1000
initiations = 10
eps = 0.001
lambda = 1.0
Klasa 3
G(x)= σ(x+β)(1-σ(x-β))
β=0.3
learningRate = 0.1
maxIterations = 1000
initiations = 10
eps = 0.001
lambda = 1.0
Klasa 4
G(x)= σ(x+β)(1-σ(x-β))
β=0.3
learningRate = 0.1
maxIterations = 1000
initiations = 10
eps = 0.001
lambda = 1.0
Klasa 5
G(x)= σ(x+β)(1-σ(x-β))
β=0.3
learningRate = 0.1
maxIterations = 1000
initiations = 10
eps = 0.001
lambda = 1.0