How mean and deviation come out with MNIST dataset?
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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
edited yesterday
timleathart
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asked yesterday
Coda ChangCoda Chang
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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
edited yesterday
timleathart
2,284827
asked yesterday
Coda ChangCoda Chang
1183
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
edited yesterday
timleathart
2,284827
asked yesterday
Coda ChangCoda Chang
1183
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.
$endgroup$
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
neural-network multilabel-classification mnist
edited yesterday
timleathart
2,284827
asked yesterday
Coda ChangCoda Chang
1183
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 yesterday
timleathart
2,284827
asked yesterday
Coda ChangCoda Chang
1183
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 yesterday
timleathart
2,284827
edited yesterday
timleathart
2,284827
edited yesterday
timleathart
2,284827
2,284827
asked yesterday
Coda ChangCoda Chang
1183
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 yesterday
Coda ChangCoda Chang
1183
asked yesterday
Coda ChangCoda Chang
1183
1183
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.
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.
Coda Chang is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
add a comment |
add a comment |
2 Answers
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mean: It is the mean of all pixel values in the dataset ( 60000 × 28 × 28 ). This mean is calculated over the whole dataset.
deviation: It is the standard deviation of all pixel values. The dataset is treated as a population rather than a sample.
What are the uses of these values?
Mean and standard deviation are commonly used to standardize the data in this case the images. Standardized data has mean close to 0 and standard deviation close to 1. You can read more here.
Why to standardize the data?
Standardization transforms your data in such a manner that it has unit variance.
According to Wikipedia,
In statistics, the standard score is the signed number of standard
deviations by which the value of an observation or data point is above
the mean value of what is being observed or measured
answered yesterday
Shubham PanchalShubham Panchal
1914
New contributor
Shubham Panchal is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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Thanks for the details
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– Coda Chang
8 hours ago
add a comment |
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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().
answered yesterday
timleatharttimleathart
2,284827
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add a comment |
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2 Answers
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2 Answers
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$begingroup$
mean: It is the mean of all pixel values in the dataset ( 60000 × 28 × 28 ). This mean is calculated over the whole dataset.
deviation: It is the standard deviation of all pixel values. The dataset is treated as a population rather than a sample.
What are the uses of these values?
Mean and standard deviation are commonly used to standardize the data in this case the images. Standardized data has mean close to 0 and standard deviation close to 1. You can read more here.
Why to standardize the data?
Standardization transforms your data in such a manner that it has unit variance.
According to Wikipedia,
In statistics, the standard score is the signed number of standard
deviations by which the value of an observation or data point is above
the mean value of what is being observed or measured
answered yesterday
Shubham PanchalShubham Panchal
1914
New contributor
Shubham Panchal is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
$begingroup$
Thanks for the details
$endgroup$
– Coda Chang
8 hours ago
add a comment |
$begingroup$
mean: It is the mean of all pixel values in the dataset ( 60000 × 28 × 28 ). This mean is calculated over the whole dataset.
deviation: It is the standard deviation of all pixel values. The dataset is treated as a population rather than a sample.
What are the uses of these values?
Mean and standard deviation are commonly used to standardize the data in this case the images. Standardized data has mean close to 0 and standard deviation close to 1. You can read more here.
Why to standardize the data?
Standardization transforms your data in such a manner that it has unit variance.
According to Wikipedia,
In statistics, the standard score is the signed number of standard
deviations by which the value of an observation or data point is above
the mean value of what is being observed or measured
answered yesterday
Shubham PanchalShubham Panchal
1914
New contributor
Shubham Panchal is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
$begingroup$
Thanks for the details
$endgroup$
– Coda Chang
8 hours ago
add a comment |
$begingroup$
mean: It is the mean of all pixel values in the dataset ( 60000 × 28 × 28 ). This mean is calculated over the whole dataset.
deviation: It is the standard deviation of all pixel values. The dataset is treated as a population rather than a sample.
What are the uses of these values?
Mean and standard deviation are commonly used to standardize the data in this case the images. Standardized data has mean close to 0 and standard deviation close to 1. You can read more here.
Why to standardize the data?
Standardization transforms your data in such a manner that it has unit variance.
According to Wikipedia,
In statistics, the standard score is the signed number of standard
deviations by which the value of an observation or data point is above
the mean value of what is being observed or measured
answered yesterday
Shubham PanchalShubham Panchal
1914
New contributor
Shubham Panchal is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
mean: It is the mean of all pixel values in the dataset ( 60000 × 28 × 28 ). This mean is calculated over the whole dataset.
deviation: It is the standard deviation of all pixel values. The dataset is treated as a population rather than a sample.
What are the uses of these values?
Mean and standard deviation are commonly used to standardize the data in this case the images. Standardized data has mean close to 0 and standard deviation close to 1. You can read more here.
Why to standardize the data?
Standardization transforms your data in such a manner that it has unit variance.
According to Wikipedia,
In statistics, the standard score is the signed number of standard
deviations by which the value of an observation or data point is above
the mean value of what is being observed or measured
answered yesterday
Shubham PanchalShubham Panchal
1914
New contributor
Shubham Panchal is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
answered yesterday
Shubham PanchalShubham Panchal
1914
New contributor
Shubham Panchal is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
answered yesterday
Shubham PanchalShubham Panchal
1914
answered yesterday
Shubham PanchalShubham Panchal
1914
1914
New contributor
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Check out our Code of Conduct.
New contributor
Shubham Panchal is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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Shubham Panchal is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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Thanks for the details
$endgroup$
– Coda Chang
8 hours ago
add a comment |
$begingroup$
Thanks for the details
$endgroup$
– Coda Chang
8 hours ago
$begingroup$
Thanks for the details
$endgroup$
– Coda Chang
8 hours ago
$begingroup$
Thanks for the details
$endgroup$
– Coda Chang
8 hours ago
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().
answered yesterday
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().
answered yesterday
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().
answered yesterday
timleatharttimleathart
2,284827
$endgroup$
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().
answered yesterday
timleatharttimleathart
2,284827
answered yesterday
timleatharttimleathart
2,284827
answered yesterday
timleatharttimleathart
2,284827
answered yesterday
timleatharttimleathart
2,284827
2,284827
add a comment |
add a comment |
Coda Chang is a new contributor. Be nice, and check out our Code of Conduct.
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Coda Chang is a new contributor. Be nice, and check out our Code of Conduct.
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