Data Augmentation for Regression ANN with low Sample Size Announcing the arrival of Valued Associate #679: Cesar Manara Planned maintenance scheduled April 23, 2019 at 00:00UTC (8:00pm US/Eastern) 2019 Moderator Election Q&A - Questionnaire 2019 Community Moderator Election ResultsImages Dataset Augmentation with fixed parameters of Crop & Rotation AngleIs image data augmentation breaking the distribution?Order of normalization / augmentation for image classificationData augmentation from directory and oriented features with KerasExpected behaviour of loss and accuracy when using data augmentationData Augmentation recommended pipelineData augmentation / feature extraction on pre-trained convnetsWhat brings the performance difference in Deep Learning with different data augmentation strategies?Is there a disadvantage to letting a model train for a large number of epochs?How to properly rotate image and labels for semantic segmentation data augmentation in Tensorflow?
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Data Augmentation for Regression ANN with low Sample Size
Announcing the arrival of Valued Associate #679: Cesar Manara
Planned maintenance scheduled April 23, 2019 at 00:00UTC (8:00pm US/Eastern)
2019 Moderator Election Q&A - Questionnaire
2019 Community Moderator Election ResultsImages Dataset Augmentation with fixed parameters of Crop & Rotation AngleIs image data augmentation breaking the distribution?Order of normalization / augmentation for image classificationData augmentation from directory and oriented features with KerasExpected behaviour of loss and accuracy when using data augmentationData Augmentation recommended pipelineData augmentation / feature extraction on pre-trained convnetsWhat brings the performance difference in Deep Learning with different data augmentation strategies?Is there a disadvantage to letting a model train for a large number of epochs?How to properly rotate image and labels for semantic segmentation data augmentation in Tensorflow?
$begingroup$
There is a Dataset of 65 tuples.
I want to Augment new Data from this set and validate my ANN on the original Data.
Is there a possibility, that my ANN already overfits on the augmentet Data. For example that the augmentation Is simulated by the ANN, and how does one prevent this ?
machine-learning regression data-augmentation
asked Nov 13 '18 at 14:53
Alexander VocaetAlexander Vocaet
133
$endgroup$
bumped to the homepage by Community♦ 25 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
$begingroup$
There is a Dataset of 65 tuples.
I want to Augment new Data from this set and validate my ANN on the original Data.
Is there a possibility, that my ANN already overfits on the augmentet Data. For example that the augmentation Is simulated by the ANN, and how does one prevent this ?
machine-learning regression data-augmentation
asked Nov 13 '18 at 14:53
Alexander VocaetAlexander Vocaet
133
$endgroup$
bumped to the homepage by Community♦ 25 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
$begingroup$
In theory it's possible, everything depends on your data, the model you're training and how you're going to augment your training data.
$endgroup$
– Mikhail Berlinkov
Nov 13 '18 at 15:34
$begingroup$
you were right. it learned the augmentation instead of the Data. I solved the problem by splitting the Dataset before augmentation and augment only a test set, and validate on data , never seen by the system.
$endgroup$
– Alexander Vocaet
Nov 15 '18 at 10:08
$begingroup$
I'll post it as the answer then if you don't mind.
$endgroup$
– Mikhail Berlinkov
Nov 16 '18 at 14:23
add a comment |
$begingroup$
There is a Dataset of 65 tuples.
I want to Augment new Data from this set and validate my ANN on the original Data.
Is there a possibility, that my ANN already overfits on the augmentet Data. For example that the augmentation Is simulated by the ANN, and how does one prevent this ?
machine-learning regression data-augmentation
asked Nov 13 '18 at 14:53
Alexander VocaetAlexander Vocaet
133
$endgroup$
There is a Dataset of 65 tuples.
I want to Augment new Data from this set and validate my ANN on the original Data.
Is there a possibility, that my ANN already overfits on the augmentet Data. For example that the augmentation Is simulated by the ANN, and how does one prevent this ?
machine-learning regression data-augmentation
machine-learning regression data-augmentation
asked Nov 13 '18 at 14:53
Alexander VocaetAlexander Vocaet
133
asked Nov 13 '18 at 14:53
Alexander VocaetAlexander Vocaet
133
asked Nov 13 '18 at 14:53
Alexander VocaetAlexander Vocaet
133
asked Nov 13 '18 at 14:53
Alexander VocaetAlexander Vocaet
133
asked Nov 13 '18 at 14:53
Alexander VocaetAlexander Vocaet
133
133
bumped to the homepage by Community♦ 25 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
bumped to the homepage by Community♦ 25 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
$begingroup$
In theory it's possible, everything depends on your data, the model you're training and how you're going to augment your training data.
$endgroup$
– Mikhail Berlinkov
Nov 13 '18 at 15:34
$begingroup$
you were right. it learned the augmentation instead of the Data. I solved the problem by splitting the Dataset before augmentation and augment only a test set, and validate on data , never seen by the system.
$endgroup$
– Alexander Vocaet
Nov 15 '18 at 10:08
$begingroup$
I'll post it as the answer then if you don't mind.
$endgroup$
– Mikhail Berlinkov
Nov 16 '18 at 14:23
add a comment |
$begingroup$
In theory it's possible, everything depends on your data, the model you're training and how you're going to augment your training data.
$endgroup$
– Mikhail Berlinkov
Nov 13 '18 at 15:34
$begingroup$
you were right. it learned the augmentation instead of the Data. I solved the problem by splitting the Dataset before augmentation and augment only a test set, and validate on data , never seen by the system.
$endgroup$
– Alexander Vocaet
Nov 15 '18 at 10:08
$begingroup$
I'll post it as the answer then if you don't mind.
$endgroup$
– Mikhail Berlinkov
Nov 16 '18 at 14:23
$begingroup$
In theory it's possible, everything depends on your data, the model you're training and how you're going to augment your training data.
$endgroup$
– Mikhail Berlinkov
Nov 13 '18 at 15:34
$begingroup$
In theory it's possible, everything depends on your data, the model you're training and how you're going to augment your training data.
$endgroup$
– Mikhail Berlinkov
Nov 13 '18 at 15:34
$begingroup$
you were right. it learned the augmentation instead of the Data. I solved the problem by splitting the Dataset before augmentation and augment only a test set, and validate on data , never seen by the system.
$endgroup$
– Alexander Vocaet
Nov 15 '18 at 10:08
$begingroup$
you were right. it learned the augmentation instead of the Data. I solved the problem by splitting the Dataset before augmentation and augment only a test set, and validate on data , never seen by the system.
$endgroup$
– Alexander Vocaet
Nov 15 '18 at 10:08
$begingroup$
I'll post it as the answer then if you don't mind.
$endgroup$
– Mikhail Berlinkov
Nov 16 '18 at 14:23
$begingroup$
I'll post it as the answer then if you don't mind.
$endgroup$
– Mikhail Berlinkov
Nov 16 '18 at 14:23
add a comment |
1 Answer
1
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oldest
votes
$begingroup$
In theory it's possible, everything depends on your data, the model you're training and how you're going to augment your training data.
answered Nov 16 '18 at 14:23
Mikhail BerlinkovMikhail Berlinkov
1916
$endgroup$
add a comment |
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$begingroup$
In theory it's possible, everything depends on your data, the model you're training and how you're going to augment your training data.
answered Nov 16 '18 at 14:23
Mikhail BerlinkovMikhail Berlinkov
1916
$endgroup$
add a comment |
$begingroup$
In theory it's possible, everything depends on your data, the model you're training and how you're going to augment your training data.
answered Nov 16 '18 at 14:23
Mikhail BerlinkovMikhail Berlinkov
1916
$endgroup$
add a comment |
$begingroup$
In theory it's possible, everything depends on your data, the model you're training and how you're going to augment your training data.
answered Nov 16 '18 at 14:23
Mikhail BerlinkovMikhail Berlinkov
1916
$endgroup$
In theory it's possible, everything depends on your data, the model you're training and how you're going to augment your training data.
answered Nov 16 '18 at 14:23
Mikhail BerlinkovMikhail Berlinkov
1916
answered Nov 16 '18 at 14:23
Mikhail BerlinkovMikhail Berlinkov
1916
answered Nov 16 '18 at 14:23
Mikhail BerlinkovMikhail Berlinkov
1916
answered Nov 16 '18 at 14:23
Mikhail BerlinkovMikhail Berlinkov
1916
1916
add a comment |
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$begingroup$
In theory it's possible, everything depends on your data, the model you're training and how you're going to augment your training data.
$endgroup$
– Mikhail Berlinkov
Nov 13 '18 at 15:34
$begingroup$
you were right. it learned the augmentation instead of the Data. I solved the problem by splitting the Dataset before augmentation and augment only a test set, and validate on data , never seen by the system.
$endgroup$
– Alexander Vocaet
Nov 15 '18 at 10:08
$begingroup$
I'll post it as the answer then if you don't mind.
$endgroup$
– Mikhail Berlinkov
Nov 16 '18 at 14:23