def get_kkmeans_model(X, X_without_contamination, train_data, num_clusters):
error_2 = 1000000
for i in xrange(1, 15):
try:
kernelKMeans = KernelKMeans(n_clusters=num_clusters,
max_iter=1000,
verbose=0,
kernel='rbf',
gamma=2**-i)
kernelKMeans.fit(X)
predict = kernelKMeans.predict(X_without_contamination)
#print predict
error = get_minimum_score(predict, train_data, num_clusters)
#print error
if error < error_2:
error_2 = error
kernelKMeans_model = kernelKMeans
gamma = 2**-i
except:
pass
kernelKMeans_model.predict(X_without_contamination)
#print gamma
#raw_input('ingrese')
return kernelKMeans_model, gamma
def get_kkmeans_model(X, X_without_contamination, train_data):
error_2 = 1000000
for i in xrange(15):
try:
kernelKMeans = KernelKMeans(n_clusters=3, max_iter=1000, verbose=0,kernel='rbf',gamma=2**-i)
kernelKMeans.fit_predict(X)
predict = kernelKMeans.predict(X_without_contamination)
error = get_minimum_score(predict,train_data)
if error < error_2 :
error_2 = error
kernelKMeans_model = kernelKMeans
gamma = 2**-i
except:
pass
return kernelKMeans_model, gamma
def get_kkmeans_model(X, X_without_contamination, train_data):
error_2 = 1000000
for i in xrange(15):
try:
kernelKMeans = KernelKMeans(n_clusters=3,
max_iter=1000,
verbose=0,
kernel='rbf',
gamma=2**-i)
kernelKMeans.fit_predict(X)
predict = kernelKMeans.predict(X_without_contamination)
error = get_minimum_score(predict, train_data)
if error < error_2:
error_2 = error
kernelKMeans_model = kernelKMeans
gamma = 2**-i
except:
pass
return kernelKMeans_model, gamma
def get_kkmeans_model(X, X_without_contamination, train_data,num_clusters):
error_2 = 1000000
for i in xrange(1,15):
try:
kernelKMeans = KernelKMeans(n_clusters=num_clusters, max_iter=1000, verbose=0,kernel='rbf',gamma=2**-i)
kernelKMeans.fit(X)
predict = kernelKMeans.predict(X_without_contamination)
#print predict
error = get_minimum_score(predict,train_data,num_clusters)
#print error
if error < error_2 :
error_2 = error
kernelKMeans_model = kernelKMeans
gamma = 2**-i
except:
pass
kernelKMeans_model.predict(X_without_contamination)
#print gamma
#raw_input('ingrese')
return kernelKMeans_model, gamma