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How mean and deviation come out with MNIST dataset?

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2

$begingroup$

I am a novice at the data science, and I notice some repository state the mean value and deviation in MNIST dataset are 0.1307 and 0.3081.

I cannot imagine how these two numbers come from. Based on my understanding, the MNIST dataset has 60,000 pics and each of them has (28 * 28 = 784) features. How do I convert this feature vectors to get the mean and deviation?

Especially, this should classify by the label, right? For example, the number 0 should have its mean and deviation. For number 1 should also have its mean and deviation.

neural-network multilabel-classification mnist

share|improve this question

edited 2 hours ago

timleathart

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2

$begingroup$

I am a novice at the data science, and I notice some repository state the mean value and deviation in MNIST dataset are 0.1307 and 0.3081.

I cannot imagine how these two numbers come from. Based on my understanding, the MNIST dataset has 60,000 pics and each of them has (28 * 28 = 784) features. How do I convert this feature vectors to get the mean and deviation?

Especially, this should classify by the label, right? For example, the number 0 should have its mean and deviation. For number 1 should also have its mean and deviation.

neural-network multilabel-classification mnist

share|improve this question

edited 2 hours ago

timleathart

2,284827

asked 4 hours ago

Coda ChangCoda Chang

1112

New contributor

Coda Chang is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

add a comment | 

$begingroup$

I am a novice at the data science, and I notice some repository state the mean value and deviation in MNIST dataset are 0.1307 and 0.3081.

I cannot imagine how these two numbers come from. Based on my understanding, the MNIST dataset has 60,000 pics and each of them has (28 * 28 = 784) features. How do I convert this feature vectors to get the mean and deviation?

Especially, this should classify by the label, right? For example, the number 0 should have its mean and deviation. For number 1 should also have its mean and deviation.

neural-network multilabel-classification mnist

share|improve this question

edited 2 hours ago

timleathart

2,284827

asked 4 hours ago

Coda ChangCoda Chang

1112

New contributor

Coda Chang is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

share|improve this question

edited 2 hours ago

timleathart

2,284827

asked 4 hours ago

Coda ChangCoda Chang

1112

New contributor

Coda Chang is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

share|improve this question

edited 2 hours ago

timleathart

2,284827

asked 4 hours ago

Coda ChangCoda Chang

1112

New contributor

Coda Chang is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

edited 2 hours ago

timleathart

2,284827

edited 2 hours ago

timleathart

2,284827

asked 4 hours ago

Coda ChangCoda Chang

1112

New contributor

Coda Chang is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

asked 4 hours ago

Coda ChangCoda Chang

1112

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$begingroup$

The repository is simply stating that amongst all features and all examples, the mean value is 0.1307 and the standard deviation is 0.3081. You can get these values yourself, if you have the mnist training set loaded into a numpy array called mnist, by simply evaluating the methods mnist.mean() and mnist.std().

share|improve this answer

answered 2 hours ago

timleatharttimleathart

2,284827

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0

$begingroup$

The repository is simply stating that amongst all features and all examples, the mean value is 0.1307 and the standard deviation is 0.3081. You can get these values yourself, if you have the mnist training set loaded into a numpy array called mnist, by simply evaluating the methods mnist.mean() and mnist.std().

share|improve this answer

answered 2 hours ago

timleatharttimleathart

2,284827

$endgroup$

add a comment | 

0

$begingroup$

The repository is simply stating that amongst all features and all examples, the mean value is 0.1307 and the standard deviation is 0.3081. You can get these values yourself, if you have the mnist training set loaded into a numpy array called mnist, by simply evaluating the methods mnist.mean() and mnist.std().

share|improve this answer

answered 2 hours ago

timleatharttimleathart

2,284827

$endgroup$

add a comment | 

$begingroup$

The repository is simply stating that amongst all features and all examples, the mean value is 0.1307 and the standard deviation is 0.3081. You can get these values yourself, if you have the mnist training set loaded into a numpy array called mnist, by simply evaluating the methods mnist.mean() and mnist.std().

share|improve this answer

answered 2 hours ago

timleatharttimleathart

2,284827

$endgroup$

share|improve this answer

answered 2 hours ago

timleatharttimleathart

2,284827

answered 2 hours ago

timleatharttimleathart

2,284827

answered 2 hours ago

timleatharttimleathart

2,284827