Databases
StackOverflow2013
Postsdbo
POHow to speed up the rjags model training in Bayesian ranking?
 

Note that there are some explanatory texts on larger screens.

plurals
  1. POHow to speed up the rjags model training in Bayesian ranking?
    primarykey
    data
    text
    <p>All, </p> <p>I am doing Bayesian modeling using rjags. However, when the number of observation is larger than 1000. The graph size is too big. </p> <p>More specifically, I am doing a Bayesian ranking problem. Traditionally, one observation means one X[i, 1:N]-Y[i] pair, where X[i, 1:N] means the i-th item is represented by a N-size predictor vector, and Y[i] is a response. The objective is to minimize the point-wise error of predicted values,for example, least square error. </p> <p>A ranking problem is different. Since we more care about the order, we use a pair-wise 1-0 indicator to represent the order between Y[i] and Y[j], for example, when Y[i]>Y[j], I(i,j)=1; otherwise I(i,j)=0. We treat this 1-0 indicator as an observation. Therefore, assuming we have K items: Y[1:K], the number of indicator is 0.5*K*(K-1). Hence when K is increased from 500 to 5000, the number of observations is very large, i.e. from 500^2 to 5000^2. The garph size of the rjags model is large too, for example graph size > 500,000. And the log-posterior will be very small. </p> <p>And it takes a long time to complete the training. I think the consumed time is >40 hours. It is not practical for me to do further experiment. Therefore, do you have any idea to speed up the rjags. I heard that the RStan is faster than Rjags. Any one who has similar experience?</p> <hr>
    singulars
    1. This table or related slice is empty.
    1. This table or related slice is empty.
    1. PTQuestion
    1. USJack Fu
    1. USJack Fu
    plurals
    1. This table or related slice is empty.
    1. This table or related slice is empty.
    1. This table or related slice is empty.
    1. This table or related slice is empty.
    1. This table or related slice is empty.
    1. COWhether Stan would be faster depends on the model. But one thing we emphasize in our comparisons between Stan and BUGS-derivatives is that the wall time to complete a fixed number of iterations is not as relevant as the number of effective samples from the posterior distribution per second. Sometimes Gibbs samplers complete many iterations in a short period of time but the draws are highly dependent and thus yield few effective samples from the posterior distribution. In any event, if JAGS isn't feasible for your problem, then you should probably give Stan a try.
      singulars
      1. POHow to speed up the rjags model training in Bayesian ranking?
      1. USBen Goodrich
    2. CO@BenGoodrich I am doing a Bayesian ranking problem. Traditionally, one observation means one X[i, 1:N]-Y[i] pair, where X[i, 1:N] means the i-th item is represented the K-predictor vector, and Y[i] is a response value. The objective is to minimize the point-wise error of predicted values,for example, least square error.
      singulars
      1. POHow to speed up the rjags model training in Bayesian ranking?
      1. USJack Fu
    3. CO@BenGoodrich A ranking problem is different. Since we more care about the order, we use a pair-wise 1-0 indicator to represent the order between Y[i] and Y[j]. We treat this 1-0 indicator as an observation. Therefore, assuming we have K items: Y[1:K], the number of indicator is 0.5*K*(K-1). Hence when K is increased from 500 to 5000, the number of observations is very large, the garph size of the rjags model is large too and the log-posterior will be very small.
      singulars
      1. POHow to speed up the rjags model training in Bayesian ranking?
      1. USJack Fu
 

Querying!

 
Guidance
A row detail

Detail views are divided into sections. All the information in the data section comes from columns in the selected row. The other sections display data from other, related rows.

Related data can be related in a to-one or a to-many fashion. Captions of data related in a to-many fashion link to a list view showing a filtered view of the table.

Try moving around until you find a non-empty to-many entry and click on the label to get to one. You can move back to the root by clicking on the database name in the header.

SQuiL has stopped working due to an internal error.

If you are curious you may find further information in the browser console, which is accessible through the devtools (F12).

Reload