Random Sampling¶
Random number generation in MXNet¶
Generate nomal distribution with mean and sd |
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Generate uniform distribution in [low, high) with specified shape |
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Set the seed used by mxnet device-specific random number generators |
Random NDArrays¶
Draw random samples from a normal (Gaussian) distribution |
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Draw random samples from an exponential distribution |
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Draw random samples from a gamma distribution |
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Draw random samples from a generalized negative binomial distribution |
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Draw random samples from a negative binomial distribution |
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Draw random samples from a normal (Gaussian) distribution |
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Computes the value of the PDF of sample of Dirichlet distributions with parameter alpha |
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Computes the value of the PDF of sample of exponential distributions with parameters lam (rate) |
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Computes the value of the PDF of sample of gamma distributions with parameters alpha (shape) and beta (rate) |
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Computes the value of the PDF of sample of generalized negative binomial distributions with parameters mu (mean) and alpha (dispersion) |
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Computes the value of the PDF of samples of negative binomial distributions with parameters k (failure limit) and p (failure probability) |
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Computes the value of the PDF of sample of normal distributions with parameters mu (mean) and sigma (standard deviation) |
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Computes the value of the PDF of sample of Poisson distributions with parameters lam (rate) |
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Computes the value of the PDF of sample of uniform distributions on the intervals given by [low,high) |
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Draw random samples from a Poisson distribution |
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Draw random samples from a discrete uniform distribution |
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Draw random samples from a uniform distribution |
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Concurrent sampling from multiple exponential distributions with parameters lambda (rate) |
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Concurrent sampling from multiple gamma distributions with parameters alpha (shape) and beta (scale) |
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Concurrent sampling from multiple generalized negative binomial distributions with parameters mu (mean) and alpha (dispersion) |
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Concurrent sampling from multiple multinomial distributions |
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Concurrent sampling from multiple negative binomial distributions with parameters k (failure limit) and p (failure probability) |
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Concurrent sampling from multiple normal distributions with parameters mu (mean) and sigma (standard deviation) |
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Concurrent sampling from multiple Poisson distributions with parameters lambda (rate) |
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Concurrent sampling from multiple uniform distributions on the intervals given by [low,high) |
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Draw random samples from a uniform distribution |
Random Symbols¶
Draw random samples from an exponential distribution |
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Draw random samples from a gamma distribution |
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Draw random samples from a generalized negative binomial distribution |
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Draw random samples from a negative binomial distribution |
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Draw random samples from a normal (Gaussian) distribution |
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Computes the value of the PDF of sample of Dirichlet distributions with parameter alpha |
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Computes the value of the PDF of sample of exponential distributions with parameters lam (rate) |
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Computes the value of the PDF of sample of gamma distributions with parameters alpha (shape) and beta (rate) |
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Computes the value of the PDF of sample of generalized negative binomial distributions with parameters mu (mean) and alpha (dispersion) |
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Computes the value of the PDF of samples of negative binomial distributions with parameters k (failure limit) and p (failure probability) |
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Computes the value of the PDF of sample of normal distributions with parameters mu (mean) and sigma (standard deviation) |
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Computes the value of the PDF of sample of Poisson distributions with parameters lam (rate) |
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Computes the value of the PDF of sample of uniform distributions on the intervals given by [low,high) |
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Draw random samples from a Poisson distribution |
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Draw random samples from a discrete uniform distribution |
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Draw random samples from a uniform distribution |
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Concurrent sampling from multiple exponential distributions with parameters lambda (rate) |
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Concurrent sampling from multiple gamma distributions with parameters alpha (shape) and beta (scale) |
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Concurrent sampling from multiple generalized negative binomial distributions with parameters mu (mean) and alpha (dispersion) |
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Concurrent sampling from multiple multinomial distributions |
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Concurrent sampling from multiple negative binomial distributions with parameters k (failure limit) and p (failure probability) |
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Concurrent sampling from multiple normal distributions with parameters mu (mean) and sigma (standard deviation) |
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Concurrent sampling from multiple Poisson distributions with parameters lambda (rate) |
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Concurrent sampling from multiple uniform distributions on the intervals given by [low,high) |
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Draw random samples from a uniform distribution |