def main():
obs = srk.Observation( np.loadtxt("data.txt") )
data_category = np.loadtxt( "category.txt" )
vae1 = vae_model( 18, epoch=200, batch_size=500 )
gmm1 = gmm.GMM( 10, category=data_category )
mm1 = mm.MarkovModel()
vae1.connect( obs )
gmm1.connect( vae1 )
mm1.connect( gmm1 )
for i in range(5):
print( i )
vae1.update()
gmm1.update()
mm1.update()
def main():
obs = srk.Observation(np.loadtxt("data.txt"))
correct_classes = np.loadtxt("correct.txt")
# GMM単体
g = gmm.GMM(4, category=correct_classes)
g.connect(obs)
g.update()
# GMMとマルコフモデルを結合したモデル
g = gmm.GMM(4, category=correct_classes)
m = mm.MarkovModel()
g.connect(obs)
m.connect(g)
for itr in range(5):
g.update()
m.update()
def main():
obs1 = srk.Observation(np.loadtxt("data1.txt"))
obs2 = srk.Observation(np.loadtxt("data2.txt"))
data_category = np.loadtxt("category.txt")
vae1 = vae_model(18, epoch=200, batch_size=500)
gmm1 = gmm.GMM(10, category=data_category)
mlda1 = mlda.MLDA(10, [200, 200], category=data_category)
mm1 = mm.MarkovModel()
vae1.connect(obs1)
gmm1.connect(vae1)
mlda1.connect(obs2, gmm1)
mm1.connect(mlda1)
for i in range(5):
print(i)
vae1.update()
gmm1.update()
mlda1.update()
mm1.update()