Hello,
-- l want to have 1000 configurations at the end of the process of gibbs sampling rather than one configuration. How can l do that properly Thank you You received this message because you are subscribed to the Google Groups "julia-stats" group. To unsubscribe from this group and stop receiving emails from it, send an email to [hidden email]. For more options, visit https://groups.google.com/d/optout. |
What function are you using? On Fri, Aug 19, 2016 at 4:23 PM, Ahmed Mazari <[hidden email]> wrote:
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CD : contrastive divergence
On Friday, August 19, 2016 at 4:30:50 PM UTC+2, Michael Borregaard wrote:
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In reply to this post by Ahmed Mazari
i have another question related to the topic. When we would like to draw a histogram for our gibbs samplaing what should be the axis of abscissa and Ordinate ?
-- On Friday, August 19, 2016 at 4:23:24 PM UTC+2, Ahmed Mazari wrote:
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l want to have 1000 configurations at the end of the process of gibbs sampling rather than one configuration. So just take 1000 samples, i.e. run `gibbs(...)` 1000 times, preferably with different input data points (`vis` parameter). Note that the idea of contrastive divergence is to reduce number of Gibbs sampling iterations per datapoint. Normally, only 1 pass is used (i.e. CD-1). i have another question related to the topic. When we would like to draw a histogram for our gibbs samplaing what should be the axis of abscissa and Ordinate ? I think the question is what you are trying to achieve. Gibbs sampling is used to produce samples from a highly multivariate distribution, so visualizing it using histograms doesn't sound very reasonable. Can you give some context of your work and reference to a library/project you are using if it's available. On Friday, August 19, 2016 at 5:45:57 PM UTC+3, Ahmed Mazari wrote:
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