Search found 284 matches

by marek [BayesFusion]
Tue Jul 28, 2020 9:13 am
Forum: SMILE
Topic: How log likelihood value is calculated in EM?
Replies: 6
Views: 70

Re: How log likelihood value is calculated in EM?

Here is the article introducing the relevance-based decomposition algorithm:

http://www.pitt.edu/~druzdzel/psfiles/uai97.pdf

I hope this helps,

Marek
by marek [BayesFusion]
Mon Jun 22, 2020 9:19 pm
Forum: GeNIe
Topic: Data Validation for an Equation-Based Model trained with Continuous Data
Replies: 1
Views: 153

Re: Data Validation for an Equation-Based Model trained with Continuous Data

Hi Njharn, I'm afraid you can't do it in GeNIe quite yet but do stay tuned. I have worked recently on a similar problem and even though I had to discretize the model variables for the purpose of structural learning, I wanted to make continuous predictions. I generated an output file in Validation an...
by marek [BayesFusion]
Tue May 19, 2020 10:45 pm
Forum: GeNIe
Topic: Reference
Replies: 1
Views: 303

Re: Reference

I will be happy to help, although I am not sure I understand your question. Are you asking how you should acknowledge us in your papers? There are a couple of examples of acknowledgments in GeNIe manual (Section "Introduction", "Copyright notice"): The models described in this paper were created usi...
by marek [BayesFusion]
Mon Apr 27, 2020 1:01 pm
Forum: GeNIe
Topic: The academy GeNIe always shut down.
Replies: 7
Views: 2284

Re: The academy GeNIe always shut down.

The size of your data set sounds manageable. When we do parameter learning, we keep the data in memory, so you need enough memory for the data (the number of bytes needed is 200K*50*8=80MB, quite small for today's computers) and for additional data structures that do not depend on the number of data...
by marek [BayesFusion]
Mon Apr 20, 2020 8:31 pm
Forum: GeNIe
Topic: The academy GeNIe always shut down.
Replies: 7
Views: 2284

Re: The academy GeNIe always shut down.

Hi Yajie, I wish I were able to write a comprehensive answer to your long query and answer every one of your questions. Regretfully, are are physically unable to offer modeling guidance to every one of our users and we have tens of thousands of them. Your best bet will be to rely on your research ad...
by marek [BayesFusion]
Wed Apr 01, 2020 10:37 am
Forum: GeNIe
Topic: Crash/error upon inference in a dynamic Bayesian network
Replies: 28
Views: 6410

Re: Crash/error upon inference in a dynamic Bayesian network

Your method is a good first cut but you are not considering the fact that before cliques are formed, the network has to be triangularized and this introduces new connections. These new connections can make cliques much larger. In fact, the size grows exponentially with the number of variables in a c...
by marek [BayesFusion]
Tue Mar 24, 2020 12:18 am
Forum: GeNIe
Topic: Crash/error upon inference in a dynamic Bayesian network
Replies: 28
Views: 6410

Re: Crash/error upon inference in a dynamic Bayesian network

HI PSGH, A general rule is that the complexity of BNs is a function of its connectivity. The number of parameters in a node goes up exponentially with the number of parents of the node. Multiply connected networks lead to complex joint trees in inference. So, the short answer is that the network com...
by marek [BayesFusion]
Mon Mar 23, 2020 7:08 pm
Forum: SMILE
Topic: Causatily VS Correlation in Bayesian Network
Replies: 1
Views: 1163

Re: Causatily VS Correlation in Bayesian Network

Let the two variables be MM and MP. I would advise having a third variable, called LS and the following structure MM<-LS->MP. If you have no data, you will have to estimate the conditional probabilities P(MM|LS) and P(MP|LS). If you have data for MM and MP, you can learn the parameters without LS be...
by marek [BayesFusion]
Fri Mar 20, 2020 1:17 pm
Forum: GeNIe
Topic: Crash/error upon inference in a dynamic Bayesian network
Replies: 28
Views: 6410

Re: Crash/error upon inference in a dynamic Bayesian network

Hi PSGH, I looked at your data set. You have only one variable measured and only one record to learn from. Is this correct? I wonder what sense this makes in theory -- I assume you know what you are doing :-). The EM algorithm has a set of complex data structures that optimize learning. It looks lik...
by marek [BayesFusion]
Wed Mar 18, 2020 10:51 pm
Forum: GeNIe
Topic: Crash/error upon inference in a dynamic Bayesian network
Replies: 28
Views: 6410

Re: Crash/error upon inference in a dynamic Bayesian network

Hi PSGH, Let me give general thoughts and then answer your specific questions. You are dealing with a problem of exponential complexity, so increasing the amount of memory will help a little but only a little. Exponential curve raises faster than you can keep up with adding more memory. Neural netwo...
by marek [BayesFusion]
Sat Mar 14, 2020 3:48 pm
Forum: GeNIe
Topic: Crash/error upon inference in a dynamic Bayesian network
Replies: 28
Views: 6410

Re: Crash/error upon inference in a dynamic Bayesian network

Hi, Your network is indeed far too complex for any implementation of Bayesian networks. SMILE may well be the most efficient and fastest piece of Bayesian network software there is but it cannot handle problems that outgrow your computer's memory. One source of complexity is the number of states in ...
by marek [BayesFusion]
Thu Feb 13, 2020 7:11 pm
Forum: GeNIe
Topic: Discrepancy between simulated CDF and discretized probabilities
Replies: 3
Views: 2025

Re: Discrepancy between simulated CDF and discretized probabilities

Got the network, thanks! I'm not sure which variable you are referring to as your outcome variable. Is it "Pconcentration mg L-1"? I tried to discretize it into more intervals to check where the samples are falling and that gave me some insight -- many samples are not really far from the bottom valu...
by marek [BayesFusion]
Thu Feb 06, 2020 5:58 pm
Forum: GeNIe
Topic: Discrepancy between simulated CDF and discretized probabilities
Replies: 3
Views: 2025

Re: Discrepancy between simulated CDF and discretized probabilities

I will be happy to try to help. I may need to play with it myself. Would you be willing to post the piece of the network in question or send it to me (Email will work best: [ADMIN: removed email to protect the innocent - please use private forum message instead]). You can obfuscate your network if y...
by marek [BayesFusion]
Tue Jul 16, 2019 9:32 am
Forum: GeNIe
Topic: Intuitive noisy averager
Replies: 4
Views: 3195

Re: Intuitive noisy averager

Cool, thanks for sharing this model with other GeNIe users. One suggestion, which is general, not necessarily about your model, as you may have other motivation for this. In the nodes "Net profit" and "Long-term biz opportunity" you have states that have zero a-priori probability. When they have zer...
by marek [BayesFusion]
Wed Jul 10, 2019 3:53 pm
Forum: GeNIe
Topic: Knowledge engineering with GeNIe
Replies: 5
Views: 3728

Re: Knowledge engineering with GeNIe

Hi Charlie, I agree with you about the need to be patient when introducing this technology -- I have been teaching it for over 25 years :-). It is not easy at first but people love it once they understand it and it solves problems for them. By the way, BayesFusion offers free 30-day evaluation of Ba...