Downsampling the dataset to create balanced dataset for neural models
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I have a classification dataset with 10k instances and 4 classes and it is unbalanced. 7000 of it belongs to first class, 2000 of it belongs to second 800 of it belongs to third class and remaining instances are belong to fourth class. I have a single neural network based on MLP.
At the end of down-sampling process, I am planning to have 2000,2000,800,200 instances. (I can even further down-sample first 3 classes until I have 200 instances from each class but I don't want to decrease size of the dataset that much).
My question is: If I train my MLP for N epoch, should I use the same subset for class-1 for all of the epochs or should I generate this subset randomly for each epoch?
neural-network scikit-learn dataset sampling
asked Sep 26 '18 at 9:34
zwlayerzwlayer
1061
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bumped to the homepage by Community♦ 12 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 |
$begingroup$
I have a classification dataset with 10k instances and 4 classes and it is unbalanced. 7000 of it belongs to first class, 2000 of it belongs to second 800 of it belongs to third class and remaining instances are belong to fourth class. I have a single neural network based on MLP.
At the end of down-sampling process, I am planning to have 2000,2000,800,200 instances. (I can even further down-sample first 3 classes until I have 200 instances from each class but I don't want to decrease size of the dataset that much).
My question is: If I train my MLP for N epoch, should I use the same subset for class-1 for all of the epochs or should I generate this subset randomly for each epoch?
neural-network scikit-learn dataset sampling
asked Sep 26 '18 at 9:34
zwlayerzwlayer
1061
$endgroup$
bumped to the homepage by Community♦ 12 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 |
$begingroup$
I have a classification dataset with 10k instances and 4 classes and it is unbalanced. 7000 of it belongs to first class, 2000 of it belongs to second 800 of it belongs to third class and remaining instances are belong to fourth class. I have a single neural network based on MLP.
At the end of down-sampling process, I am planning to have 2000,2000,800,200 instances. (I can even further down-sample first 3 classes until I have 200 instances from each class but I don't want to decrease size of the dataset that much).
My question is: If I train my MLP for N epoch, should I use the same subset for class-1 for all of the epochs or should I generate this subset randomly for each epoch?
neural-network scikit-learn dataset sampling
asked Sep 26 '18 at 9:34
zwlayerzwlayer
1061
$endgroup$
I have a classification dataset with 10k instances and 4 classes and it is unbalanced. 7000 of it belongs to first class, 2000 of it belongs to second 800 of it belongs to third class and remaining instances are belong to fourth class. I have a single neural network based on MLP.
At the end of down-sampling process, I am planning to have 2000,2000,800,200 instances. (I can even further down-sample first 3 classes until I have 200 instances from each class but I don't want to decrease size of the dataset that much).
My question is: If I train my MLP for N epoch, should I use the same subset for class-1 for all of the epochs or should I generate this subset randomly for each epoch?
neural-network scikit-learn dataset sampling
neural-network scikit-learn dataset sampling
asked Sep 26 '18 at 9:34
zwlayerzwlayer
1061
asked Sep 26 '18 at 9:34
zwlayerzwlayer
1061
asked Sep 26 '18 at 9:34
zwlayerzwlayer
1061
asked Sep 26 '18 at 9:34
zwlayerzwlayer
1061
asked Sep 26 '18 at 9:34
zwlayerzwlayer
1061
1061
bumped to the homepage by Community♦ 12 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♦ 12 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 |
add a comment |
1 Answer
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You will get better results if you change subset of images from downsampled class randomly at each epoch. It will help in building a robust model as well. And use data augmentation techniques for minor classes.
answered Sep 26 '18 at 10:24
Poonam LigadePoonam Ligade
413
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$begingroup$
I guess you missed my question. I am not asking how to balanced my dataset, I am asking should I changed my down-sampled class at each epoch or keep it same during traning of my neural net.
$endgroup$
– zwlayer
Sep 26 '18 at 11:02
add a comment |
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1 Answer
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1 Answer
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$begingroup$
You will get better results if you change subset of images from downsampled class randomly at each epoch. It will help in building a robust model as well. And use data augmentation techniques for minor classes.
answered Sep 26 '18 at 10:24
Poonam LigadePoonam Ligade
413
$endgroup$
$begingroup$
I guess you missed my question. I am not asking how to balanced my dataset, I am asking should I changed my down-sampled class at each epoch or keep it same during traning of my neural net.
$endgroup$
– zwlayer
Sep 26 '18 at 11:02
add a comment |
$begingroup$
You will get better results if you change subset of images from downsampled class randomly at each epoch. It will help in building a robust model as well. And use data augmentation techniques for minor classes.
answered Sep 26 '18 at 10:24
Poonam LigadePoonam Ligade
413
$endgroup$
$begingroup$
I guess you missed my question. I am not asking how to balanced my dataset, I am asking should I changed my down-sampled class at each epoch or keep it same during traning of my neural net.
$endgroup$
– zwlayer
Sep 26 '18 at 11:02
add a comment |
$begingroup$
You will get better results if you change subset of images from downsampled class randomly at each epoch. It will help in building a robust model as well. And use data augmentation techniques for minor classes.
answered Sep 26 '18 at 10:24
Poonam LigadePoonam Ligade
413
$endgroup$
You will get better results if you change subset of images from downsampled class randomly at each epoch. It will help in building a robust model as well. And use data augmentation techniques for minor classes.
answered Sep 26 '18 at 10:24
Poonam LigadePoonam Ligade
413
edited Sep 26 '18 at 11:24
answered Sep 26 '18 at 10:24
Poonam LigadePoonam Ligade
413
answered Sep 26 '18 at 10:24
Poonam LigadePoonam Ligade
413
answered Sep 26 '18 at 10:24
Poonam LigadePoonam Ligade
413
413
$begingroup$
I guess you missed my question. I am not asking how to balanced my dataset, I am asking should I changed my down-sampled class at each epoch or keep it same during traning of my neural net.
$endgroup$
– zwlayer
Sep 26 '18 at 11:02
add a comment |
$begingroup$
I guess you missed my question. I am not asking how to balanced my dataset, I am asking should I changed my down-sampled class at each epoch or keep it same during traning of my neural net.
$endgroup$
– zwlayer
Sep 26 '18 at 11:02
$begingroup$
I guess you missed my question. I am not asking how to balanced my dataset, I am asking should I changed my down-sampled class at each epoch or keep it same during traning of my neural net.
$endgroup$
– zwlayer
Sep 26 '18 at 11:02
$begingroup$
I guess you missed my question. I am not asking how to balanced my dataset, I am asking should I changed my down-sampled class at each epoch or keep it same during traning of my neural net.
$endgroup$
– zwlayer
Sep 26 '18 at 11:02
add a comment |
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