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Number of iterations as a hyper-parameter in neural network [closed]
How to determine what's the optimal number of iterations in learning a neural network?
python neural-network
asked Jan 1 at 18:24
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closed as too broad by Carcigenicate, Matias Valdenegro, tripleee, gnat, desertnaut Jan 12 at 14:16
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How to determine what's the optimal number of iterations in learning a neural network?
python neural-network
asked Jan 1 at 18:24
AvocanoAvocano
367
closed as too broad by Carcigenicate, Matias Valdenegro, tripleee, gnat, desertnaut Jan 12 at 14:16
Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer. Avoid asking multiple distinct questions at once. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.
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How to determine what's the optimal number of iterations in learning a neural network?
python neural-network
asked Jan 1 at 18:24
AvocanoAvocano
367
How to determine what's the optimal number of iterations in learning a neural network?
python neural-network
python neural-network
asked Jan 1 at 18:24
AvocanoAvocano
367
asked Jan 1 at 18:24
AvocanoAvocano
367
asked Jan 1 at 18:24
AvocanoAvocano
367
asked Jan 1 at 18:24
AvocanoAvocano
367
asked Jan 1 at 18:24
AvocanoAvocano
367
367
closed as too broad by Carcigenicate, Matias Valdenegro, tripleee, gnat, desertnaut Jan 12 at 14:16
Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer. Avoid asking multiple distinct questions at once. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.
closed as too broad by Carcigenicate, Matias Valdenegro, tripleee, gnat, desertnaut Jan 12 at 14:16
Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer. Avoid asking multiple distinct questions at once. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.
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1 Answer
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One way of doing it is to split your training data into a train and validation set. During training, the error on the training set should decrease steadily. The error on the validation set will decrease and at some point start to increase again. At this point the net starts to overfit to the training data. What that means is that the model adapts to the random variations in the data rather than learning the true regularities. You should retain the model with overall lowest validation error. This is called Early Stopping.
Alternatively, you can use Dropout. With a high enough Dropout probability, you can essentially train for as long as you want, and overfitting will not be a significant issue.
answered Jan 1 at 18:28
braaterAfrikaanerbraaterAfrikaaner
1,062517
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
One way of doing it is to split your training data into a train and validation set. During training, the error on the training set should decrease steadily. The error on the validation set will decrease and at some point start to increase again. At this point the net starts to overfit to the training data. What that means is that the model adapts to the random variations in the data rather than learning the true regularities. You should retain the model with overall lowest validation error. This is called Early Stopping.
Alternatively, you can use Dropout. With a high enough Dropout probability, you can essentially train for as long as you want, and overfitting will not be a significant issue.
answered Jan 1 at 18:28
braaterAfrikaanerbraaterAfrikaaner
1,062517
add a comment |
One way of doing it is to split your training data into a train and validation set. During training, the error on the training set should decrease steadily. The error on the validation set will decrease and at some point start to increase again. At this point the net starts to overfit to the training data. What that means is that the model adapts to the random variations in the data rather than learning the true regularities. You should retain the model with overall lowest validation error. This is called Early Stopping.
Alternatively, you can use Dropout. With a high enough Dropout probability, you can essentially train for as long as you want, and overfitting will not be a significant issue.
answered Jan 1 at 18:28
braaterAfrikaanerbraaterAfrikaaner
1,062517
add a comment |
One way of doing it is to split your training data into a train and validation set. During training, the error on the training set should decrease steadily. The error on the validation set will decrease and at some point start to increase again. At this point the net starts to overfit to the training data. What that means is that the model adapts to the random variations in the data rather than learning the true regularities. You should retain the model with overall lowest validation error. This is called Early Stopping.
Alternatively, you can use Dropout. With a high enough Dropout probability, you can essentially train for as long as you want, and overfitting will not be a significant issue.
answered Jan 1 at 18:28
braaterAfrikaanerbraaterAfrikaaner
1,062517
One way of doing it is to split your training data into a train and validation set. During training, the error on the training set should decrease steadily. The error on the validation set will decrease and at some point start to increase again. At this point the net starts to overfit to the training data. What that means is that the model adapts to the random variations in the data rather than learning the true regularities. You should retain the model with overall lowest validation error. This is called Early Stopping.
Alternatively, you can use Dropout. With a high enough Dropout probability, you can essentially train for as long as you want, and overfitting will not be a significant issue.
answered Jan 1 at 18:28
braaterAfrikaanerbraaterAfrikaaner
1,062517
edited Jan 1 at 18:51
answered Jan 1 at 18:28
braaterAfrikaanerbraaterAfrikaaner
1,062517
answered Jan 1 at 18:28
braaterAfrikaanerbraaterAfrikaaner
1,062517
answered Jan 1 at 18:28
braaterAfrikaanerbraaterAfrikaaner
1,062517
1,062517
add a comment |
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