BayesFusion Support Forum

Hi,

thank you for your updates. Currently I am working on a different project, but as soon as I get back to the other one I will let you know the differences.

Regards,

Christian

Hello Marc,

I want to let you know, that the Genie Training is now finished.

The networks, Training data, computer usage - everything was the same.

Old Training Time: 1864 minutes
New Training time: 1348 minutes

It is an improvement of 28%. This way I will get about every third network training ...

Thank you!

Thank you for your updates. For Batch Training I am using smile.net. This one is not updated yet.

But I will start training of the same network with the same data now and will let you know how much the improovements are in this sample. I don't know how much it can take. This network took the last ...

Yes, calculating would be a disadvantage. But as I will have precalculated every possible evidence settings (for speed enhancement) it is not that problem for me.

Thank you for both.

As far as I have tested it my approach for soft evidence seems to work. So I will use it in production environment. It is easier to implement that your demonstrated soft evidence as I can use it with every node without adaptations.

As soon as the new Genie/Smile Version is ...

Ah, okay. I am already doing that. I have three networks. Then I first calculate network one and use the result in network two. To do so I am using simulated soft evidence I described here:


By the way, to simulate soft evidence I have found a good way:

For example if I want to set 30% state1 and ...

Oh, thats sad. But when I am using smile.net and running this on Windows using the x64 Version of DotNet then this smile.net version should also running in 64 bit mode and so I should be able to use the bigger memory?

Hello Marc,

1-2 times faster sounds great.

About entering precision: I am sure that I will enter everytime highest precision as otherwise I could never be sure if a wrong net data is based on stopping em-algorithm to early.

So I would not use this option.

But if you want to implement something ...

Yes exactly.

Or if you want to use 100% the same data count as I have used:

1.157.000 Datasets with Node1 to Node8, Node9 to Node 13 empty
237.000 Datasets with data for Node1 to Node13

so:

83% Datasets with Node1 to Node8. Node9 to Node13 is empty
17% Datasets with all Data from Node1 to ...

lol, top to right. I meant top to bottom. I should go to bed

Yes, I mean the diagonals. Okay. Now it is right.

sorry, yes - I have mistakenly confised rows and columns. I am taking about the ones going from top to right

AFAIK if you set missing value to 80% then randomly 80% of the data is missing. But that is not the true data source. Row 1-8 has 100% data and row 9 to 13 about 20%.

if you set the missing value to 80% then everywhere data is missing, not only node 9 to 13. At least this is what I interpret the ...

Hello Marc,

I have prepared both networks. I am just compressing them and will upload them via rapidshare. I will send you the link via pm.

I really hope it helps to improve Genies EM-Algorithm implementation.

When you write the software that eliminates about 80 percent of the dataset, maybe you ...

Thank you for your offer. I think you were right with the assumption that the training took longer because the values had problems to convert to optimum.

I had two nodes with each 6 different incoming connection from other nodes. Lets call these two nodes getting all those incoming nodes root nodes ...