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configSample.yaml
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configSample.yaml
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resultDirName: 'DANESample'
movies617:
layers: [512,128,16]
View_num: 2
ft_times: 500
beta_W: [10,10,10]
L: [0.001,0.01,0.1,1,10,100]
alpha: [0.001,0.01,0.1,1,10,100]
gama: [0.001,0.01,0.1,1,10,100]
batch_size: 617
pretrain: False
learning_rate: [0.0001] #[0.001,0.0001,0.00001,0.000001,0.0000001]
sent_outputs_norm: True
cora:
layers: [512,128,16]
View_num: 2
ft_times: 500
beta_W: [50,60]
L: [0.1]
alpha: [0.1]
gama: [100]
batch_size: 256
pretrain: False
learning_rate: [0.000001] #[0.0001] #
sent_outputs_norm: True
BBCSport:
loadW: False
layers: [256,64,16]
View_num: 2
ft_times: 1000
beta_W: [10,10,10]
L: [0.1]
alpha: [0.001]
gama: [100]
batch_size: 256
pretrain: False
learning_rate: [0.00001] #[0.0001] #
sent_outputs_norm: True
Digits76240:
layers: [512,128,32]
View_num: 2
ft_times: 100
beta_W: [10,10,10]
L: [0.1]
alpha: [0.001]
gama: [100]
batch_size: 2000
pretrain: False
learning_rate: [0.000001] #[0.0001] #
sent_outputs_norm: False
100leaves:
loadW: True
layers: [500,100]
View_num: 3
ft_times: 1000
beta_W: [0,1,5,10,20,30,40,50,60,70,80,90,100]
L: [0.1]
alpha: [0.001]
gama: [100]
batch_size: 1600
pretrain: False
learning_rate: [0.000001] #[0.0001] #
sent_outputs_norm: True
NUSWIDEOBJ:
loadW: True
layers: [ 512,128,32 ]
View_num: 5
ft_times: 100
beta_W: [0,1,5,10,20,30,40,50,60,70,80,90,100]
L: [0.1]
alpha: [0.001]
gama: [100]
batch_size: 256
pretrain: True
learning_rate: [ 0.00001 ] #[0.0001] #
sent_outputs_norm: True
Caltech101-all:
loadW: False
layers: [512, 128, 32]
View_num: 6
ft_times: 500
beta_W: [0,1,10]
L: [0.1]
alpha: [0.001]
gama: [100]
batch_size: 1000
pretrain: False
learning_rate: [ 0.0001 ] #[0.0001] #
sent_outputs_norm: True
ALOI_100:
loadW: True
layers: [500,200,100] #[500,100]
View_num: 4
ft_times: 1000
beta_W: [0,1,5,10,20,30,40,50,60,70,80,90,100]
L: [ 0.1 ]
alpha: [ 0.001 ]
gama: [ 100 ]
batch_size: 300
pretrain: False
learning_rate: [ 0.0001 ] #[0.0001] #
sent_outputs_norm: True