BayesFusion Support Forum

Thank you for your information for setting seed using network properties.

Before, I was setting seed using the following code, which does not work.

```
random.seed(seed)
np.random.seed(seed)
```

I tried just now using method `pysmile.Network.set_rand_seed`

```
model.set_rand_seed(seed)
```

I ...

Dear Community,

I am following the PDF version of the tutorial for SMILE wrappers, specifically for python language.

I am try SMILE package on our real-world dataset.

Since the real world dataset is too big. I have to use "pysmile.BayesianAlgorithmType.EPIS_SAMPLING" to produce inference ...

Hi,

"set explicit targets in the network if you're only interested in the subset of node probabilities"

print_posteriors() function is like below:

def print_posteriors(net, node_handle):
node_id = net.get_node_id(node_handle)
if net.is_evidence(node_handle):
print(f"{node_id} has evidence ...

Dear Community,

I am following the PDF version of the tutorial for SMILE wrappers, specifically for python language.


I am trying SMILE package on our real-world dataset.

Our dataset has 1654 nodes, 2965 edges.
Among the 1654 nodes, there are 605 continuous variables and 1049 categorical ...

Hi, I have a following up question:

Does SMILE support inference on hybrid network?
Suppose we learn the parameter in some other way. Can we encode the learned parameter in the hybrid network and then we do inference or manipulation of variables on it?

For instance, there is a case a discrete ...

Thanks, I have read "GeNIe manual, chapter 'Controlling values'". it is clear to me now.

Can I ask a further question?
I search both GeNIe manual and Wrapper manual.
I did not find the document to introduce how to use the function `Network.set_controlled_value`.

Could you please instruct me ...

We want to use SMILE to do manipulation for a variable, and see how the manipulation can affect the target variable.

Here is a brief explanation of the difference between "observing" and "manipulation/intervening".

Given a graph B -> A, A -> T, B -> T.

In Tutorial 2, if we use function `change ...

Dear Support team,

I am following the PDF version of the tutorial for SMILE wrappers, specifically for the Python language.

Is there a way to output goodness-of-fit metric such as BIC, log likelihood score, given a predefined network structure and a dataset?

BIC score (Bayesian Information ...

Dear Support team,

I am following the PDF version of the tutorial for SMILE wrappers, specifically for the Python language.

I tried to simulate a hybrid network (with both discrete and continuous variables).

I first predefined a network structure and then simulated a dataset. I tried to use ...

Dear Community,

I am following the PDF version of the tutorial for SMILE wrappers, specifically for the Python language.

To simulate a dataset from a hybrid Bayesian network with both categorical and continuous variables, we need to:

Define the conditional probability tables (CPTs) for ...

Thank you shooltz[BayesFusion].
I have installed and tested, and it looks good.

Just to confirm, after I installed the whl file using the command `pip install [whl file]`, the .so file automatically appears in my Python virtual environment package folder.
So, I do not need to do anything with ...

Hi, here is the Linux information for the cluster, using command cat /etc/os-release :


NAME="Rocky Linux"
VERSION="8.10 (Green Obsidian)"
ID="rocky"
ID_LIKE="rhel centos fedora"
VERSION_ID="8.10"
PLATFORM_ID="platform:el8"
PRETTY_NAME="Rocky Linux 8.10 (Green Obsidian)"
ANSI_COLOR="0;32"
LOGO ...

I am using the 2.4.0 version of pysmile.


Name: pysmile Version: 2.4.0
Summary: BayesFusion's SMILE wrapper
Home-page: [https://bayesfusion.com/](https://bayesfusion.com/)
Author: BayesFusion LLC Author-email: support@bayesfusion.com


In my local machine, my Linux is cutting edge, and there ...

cont_net = pysmile.Network()

# Here the node is not added in order ABCD, but CABD
C = create_cont_node(cont_net, "C", "C", 10, 40)
A = create_cont_node(cont_net, "A", "A", 10, 20)
B = create_cont_node(cont_net, "B", "B", 10, 30)
D = create_cont_node(cont_net, "D", "D", 10, 50)

cont_net.add_arc(C ...

Let us discuss this section of the code below:


em = pysmile.learning.EM()

try:
matching = cate_ds.match_network(cate_net)
except pysmile.SMILEException:
print("Can't automatically match network with dataset")
#endtry

em.set_uniformize_parameters(False)
em.set_randomize_parameters(False)
em ...