Search found 433 matches
- Fri May 24, 2024 7:12 pm
- Forum: GeNIe
- Topic: why 'learning a new network' cannot capture relationships?
- Replies: 4
- Views: 38
Re: why 'learning a new network' cannot capture relationships?
The Bayesian Search-based algorithms (Bayesian Search and GTT) learn no arcs, PC and Naive Bayes-based algorithms (NB, TAN and ANB) show plenty of dependencies. With 12 data records, whatever you will learn in terms of structure will be completely unreliable. Naive Bayes may do best if one of your v...
- Thu May 16, 2024 2:32 pm
- Forum: GeNIe
- Topic: Can the parameters of a DBN be learnt from "regular" time series data sets?
- Replies: 2
- Views: 51
Re: Can the parameters of a DBN be learnt from "regular" time series data sets?
Please note that there are many ways in which you can transform the data set to make it suitable for learning. Essentially, the first decision that you need to make is what order your model is, i.e., what is the highest time degree of a link in your model. You will reflect your decision in the struc...
- Tue May 14, 2024 9:04 am
- Forum: SMILE
- Topic: clearEvidence without removing other nodes probabilities
- Replies: 3
- Views: 110
Re: clearEvidence without removing other nodes probabilities
I have read your post but have frankly difficulties in understanding what precisely you want to do from the theoretical perspective. What I understand, perhaps wrongly, is that you would like to observe a node, calculate the impact of that observation, but then clear the observation but preserve its...
- Tue Mar 12, 2024 6:39 pm
- Forum: GeNIe
- Topic: Strange behavior of TruncNormal
- Replies: 7
- Views: 2187
Re: Strange behavior of TruncNormal
In GeNIe, you can see all samples generated on the left hand side in the Value tab. GeNIe displays the number of samples generated for any bar in the histogram when you hover over that bar. Distribution visualizer has the same functionality. We will extend the description in the manual to account fo...
- Sat Mar 02, 2024 9:44 pm
- Forum: GeNIe
- Topic: Strange behavior of TruncNormal
- Replies: 7
- Views: 2187
Re: Strange behavior of TruncNormal
You are proposing an interesting solution that will work well in many case, certainly in this case. Let us look at the simplified model with just three variables. We do get funny (in terms of being large) number of samples in forward inference for small and large values of evidence in v1 (e.g., 0..1...
- Tue Feb 27, 2024 8:21 pm
- Forum: GeNIe
- Topic: Strange behavior of TruncNormal
- Replies: 7
- Views: 2187
Re: Strange behavior of TruncNormal
I have looked at your model and I believe that this is a theoretical problem that is solvable at the modeling stage. Please note that the domain of v2 is {0,10} and when you have a combination of {0,1} at v1 and {-2,-1} at error, you generate a value for v2 that is out of bounds. This is handled eas...
- Fri Dec 15, 2023 3:38 pm
- Forum: GeNIe
- Topic: Coding boolean statements
- Replies: 2
- Views: 2221
Re: Coding boolean statements
Hi Fabrice, What you want to do mixes values (high, moderate, and low) with uncertainty about them (probability of "low" > 0.7). Bayesian networks are models consisting of variables, each of which has its domain (these are values), and interactions among them, which can be best thought of ...
- Fri Nov 24, 2023 9:42 pm
- Forum: GeNIe
- Topic: enter evidence, virtual evidence, and controlling values
- Replies: 4
- Views: 2600
Re: enter evidence, virtual evidence, and controlling values
Hi Yan, Yes, you are correct in that if you want to see the effect of both sport and drinking water, you should control both. In the example that you gave, the effect on health of controlling both will be the same as the effect of observing both. In fact, you can see the effect in the CPT for node C...
- Thu Nov 23, 2023 2:37 pm
- Forum: GeNIe
- Topic: enter evidence, virtual evidence, and controlling values
- Replies: 4
- Views: 2600
Re: enter evidence, virtual evidence, and controlling values
Hi Yan, Let me try to answer your questions. 1. My understanding is that entering evidence can only give 100% for one state of node A, while virtual evidence can give the probability distribution (e.g., 20%, 40%, 40%, assuming there are three states) for all states of node A. Is it right? If so, doe...
- Tue Oct 31, 2023 9:37 pm
- Forum: GeNIe
- Topic: max sensitivity Genie 2.4
- Replies: 4
- Views: 3529
Re: max sensitivity Genie 2.4
Hi Camilla, I'd love to look at this model to make sure that I am understanding your question correctly. Perhaps we can meet online? Please shoot me a private message so that we can set the time. Alternatively, perhaps you can share with me the relevant part of the model? You can use GeNIe obfuscati...
- Tue Oct 10, 2023 4:30 pm
- Forum: GeNIe
- Topic: Log-transformation data
- Replies: 2
- Views: 2321
Re: Log-transformation data
You can't do it in GeNIe. What you can do is transform your data in Excel by creating for a variable x a new variable/column named, e.g., log_x) and then save the file as .CSV and load it into GeNIe. You can use log_x instead of x in learning.
I hope this helps,
Marek
I hope this helps,
Marek
- Fri Sep 15, 2023 8:46 pm
- Forum: GeNIe
- Topic: structure learning
- Replies: 4
- Views: 2845
Re: structure learning
Hi Yan, I have looked at your data and have managed to replicate the problem. Clearly, there is a bug in PC and, as you wrote, the algorithm ignores the max. adjacency size parameter. We will work on it and will fix it in the next release. When I face a problem like yours, I usually play with the al...
- Thu Sep 14, 2023 1:02 pm
- Forum: GeNIe
- Topic: structure learning
- Replies: 4
- Views: 2845
Re: structure learning
Hi Yan, Let me try to answer your questions. (1) This is hard to say, as the two algorithms work on different principles. I would try both and look for commonalities in the output. This especially that your data set is rather small. Please play with the significance level alpha in PC -- it has a big...
- Fri Sep 08, 2023 12:47 pm
- Forum: GeNIe
- Topic: Combining expert elicitation and emprical data
- Replies: 2
- Views: 2548
Re: Combining expert elicitation and emprical data
Absolutely! This is in fact what we have been advising when the data set is small (a "small data set" is, of course, a relative term and depends on the complexity of the network but we are dealing with too small data sets most of the time :-)). You can start with a rough estimation of the ...
- Fri Jun 09, 2023 7:28 pm
- Forum: GeNIe
- Topic: parameter learning and validation in GeNIe 4.0 vs 3.0
- Replies: 3
- Views: 3262
Re: parameter learning and validation in GeNIe 4.0 vs 3.0
I believe that case counting should be at least as good as the EM algorithm. It is a special case of EM.
I hope this helps,
Marek
I hope this helps,
Marek