How to normalize LSTM input data in Keras with BatchNormalization
I have my neural network constructed like the following:
tempIn = Input(shape = (None, 4))
tempModel = LSTM(data.xRnnLosFeatures)(tempIn)
tempModel = BatchNormalization()(tempModel)
tempModel = Activation('tanh')(tempModel)
tempModel = Dropout(0.5)(tempModel)
tempModel = Dense(1)(tempModel)
model = Model(inputs=tempIn, outputs=tempModel)
However, I keep getting a very large error if I do not manually normalize my input data before I feed this network. What is a way to normalize my input data correctly. I tried to add another one before LSTM layer but that doesn't work. Thanks!
python keras
edited Nov 13 '18 at 5:06
Joel
1,5706719
asked Nov 13 '18 at 0:44
vvofdcxvvofdcx
94114
add a comment |
I have my neural network constructed like the following:
tempIn = Input(shape = (None, 4))
tempModel = LSTM(data.xRnnLosFeatures)(tempIn)
tempModel = BatchNormalization()(tempModel)
tempModel = Activation('tanh')(tempModel)
tempModel = Dropout(0.5)(tempModel)
tempModel = Dense(1)(tempModel)
model = Model(inputs=tempIn, outputs=tempModel)
However, I keep getting a very large error if I do not manually normalize my input data before I feed this network. What is a way to normalize my input data correctly. I tried to add another one before LSTM layer but that doesn't work. Thanks!
python keras
edited Nov 13 '18 at 5:06
Joel
1,5706719
asked Nov 13 '18 at 0:44
vvofdcxvvofdcx
94114
add a comment |
I have my neural network constructed like the following:
tempIn = Input(shape = (None, 4))
tempModel = LSTM(data.xRnnLosFeatures)(tempIn)
tempModel = BatchNormalization()(tempModel)
tempModel = Activation('tanh')(tempModel)
tempModel = Dropout(0.5)(tempModel)
tempModel = Dense(1)(tempModel)
model = Model(inputs=tempIn, outputs=tempModel)
However, I keep getting a very large error if I do not manually normalize my input data before I feed this network. What is a way to normalize my input data correctly. I tried to add another one before LSTM layer but that doesn't work. Thanks!
python keras
edited Nov 13 '18 at 5:06
Joel
1,5706719
asked Nov 13 '18 at 0:44
vvofdcxvvofdcx
94114
I have my neural network constructed like the following:
tempIn = Input(shape = (None, 4))
tempModel = LSTM(data.xRnnLosFeatures)(tempIn)
tempModel = BatchNormalization()(tempModel)
tempModel = Activation('tanh')(tempModel)
tempModel = Dropout(0.5)(tempModel)
tempModel = Dense(1)(tempModel)
model = Model(inputs=tempIn, outputs=tempModel)
However, I keep getting a very large error if I do not manually normalize my input data before I feed this network. What is a way to normalize my input data correctly. I tried to add another one before LSTM layer but that doesn't work. Thanks!
python keras
python keras
edited Nov 13 '18 at 5:06
Joel
1,5706719
asked Nov 13 '18 at 0:44
vvofdcxvvofdcx
94114
edited Nov 13 '18 at 5:06
Joel
1,5706719
asked Nov 13 '18 at 0:44
vvofdcxvvofdcx
94114
edited Nov 13 '18 at 5:06
Joel
1,5706719
edited Nov 13 '18 at 5:06
Joel
1,5706719
edited Nov 13 '18 at 5:06
Joel
1,5706719
1,5706719
asked Nov 13 '18 at 0:44
vvofdcxvvofdcx
94114
asked Nov 13 '18 at 0:44
vvofdcxvvofdcx
94114
asked Nov 13 '18 at 0:44
vvofdcxvvofdcx
94114
94114
add a comment |
add a comment |
1 Answer
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active
oldest
votes
You can use the keras normalise function or alternatively you could use scikit-learn preprocessing function.
edited Dec 30 '18 at 23:32
Loss of human identity
1,1571922
answered Dec 30 '18 at 22:15
user8355515user8355515
1
You should explain in detail how to use the functions that you've mentioned in the context of the question being asked, rather than simply saying those functions exist and can be used.
– anothermh
Dec 30 '18 at 22:50
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
You can use the keras normalise function or alternatively you could use scikit-learn preprocessing function.
edited Dec 30 '18 at 23:32
Loss of human identity
1,1571922
answered Dec 30 '18 at 22:15
user8355515user8355515
1
You should explain in detail how to use the functions that you've mentioned in the context of the question being asked, rather than simply saying those functions exist and can be used.
– anothermh
Dec 30 '18 at 22:50
add a comment |
You can use the keras normalise function or alternatively you could use scikit-learn preprocessing function.
edited Dec 30 '18 at 23:32
Loss of human identity
1,1571922
answered Dec 30 '18 at 22:15
user8355515user8355515
1
You should explain in detail how to use the functions that you've mentioned in the context of the question being asked, rather than simply saying those functions exist and can be used.
– anothermh
Dec 30 '18 at 22:50
add a comment |
You can use the keras normalise function or alternatively you could use scikit-learn preprocessing function.
edited Dec 30 '18 at 23:32
Loss of human identity
1,1571922
answered Dec 30 '18 at 22:15
user8355515user8355515
1
You can use the keras normalise function or alternatively you could use scikit-learn preprocessing function.
edited Dec 30 '18 at 23:32
Loss of human identity
1,1571922
answered Dec 30 '18 at 22:15
user8355515user8355515
1
edited Dec 30 '18 at 23:32
Loss of human identity
1,1571922
edited Dec 30 '18 at 23:32
Loss of human identity
1,1571922
edited Dec 30 '18 at 23:32
Loss of human identity
1,1571922
1,1571922
answered Dec 30 '18 at 22:15
user8355515user8355515
1
answered Dec 30 '18 at 22:15
user8355515user8355515
1
answered Dec 30 '18 at 22:15
user8355515user8355515
1
1
You should explain in detail how to use the functions that you've mentioned in the context of the question being asked, rather than simply saying those functions exist and can be used.
– anothermh
Dec 30 '18 at 22:50
add a comment |
You should explain in detail how to use the functions that you've mentioned in the context of the question being asked, rather than simply saying those functions exist and can be used.
– anothermh
Dec 30 '18 at 22:50
You should explain in detail how to use the functions that you've mentioned in the context of the question being asked, rather than simply saying those functions exist and can be used.
– anothermh
Dec 30 '18 at 22:50
You should explain in detail how to use the functions that you've mentioned in the context of the question being asked, rather than simply saying those functions exist and can be used.
– anothermh
Dec 30 '18 at 22:50
add a comment |
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