nnet | Neural networks in NumPy/Cython | Machine Learning library

What are your preferred techniques for combining a table with a plot in one image using R? I remember using tableGrob() and either patchwork or cowplot months ago but cannot remember the details.

This example uses the ggstatsplot package. I would like to add the correlation coefficients to the correlogram (correlation plot).

I'm trying to configure a simple network structure using Vagrant as depicted in the following figure:

As you can see I aim to simulate a hacker attack which goes from attacker through router and reaches victim, but that's not important for the problem I'm struggling with.

This is my Vagrantfile so far (VritualBox is used as provider):

I am wanting to build a neural network classifier using the caret package. I have specified a tunegrid with some hyper-parameters that I want to test to get the best accuracy.

After I run the model, the train function function will always default to the standard decay and size values. Is this a bug within caret? or is there an issue with my code?

Code:

I am trying to figure out what is wrong with my initialization of the neural network model. I have already set a pdb trace to see that the defining neural network part is the source of error. Also, I get yellow marks on the defining neural network code because the module is expected to be returned but if I return the module, it causes a recursion error. It is a linear model that has to have an input dimension of the batch size * 81 and an output dimension of the batch size * 1. I am relatively new at pytorch and defining deep neural networks so this may not be a good question. My syntax may also be very bad. Any help is appreciated. The code below is the defining of the neural network and training of the pytorch model.

So I have several examples of raw text in which I have to extract the characters after 'Terms'. The common pattern I see is after the word 'Terms' there is a '\n' and also at the end '\n' I want to extract all the characters(words, numbers, symbols) present between these to \n but after keyword 'Terms'.

Some examples of text are given below:

I want to fit a multinomial model with nnet::multinom() and get predictions with ggeffects::ggemmeans(). Whereas such procedure works in regular code, I fail to wrap this in a function.

Data

I have been training some models and when I try to use Support Vector Machines with Radial Basis Function Kernel I get the following error:

While reading the PDF table using camelot some columns are concatenated and their values too like below

This question is a bit confusing so bear with me, it also has to be done with pure Python and no third-party modules.

I can't seem to assign the correct datatype to the CSV values and assign them to the class attributes.

I've tried every way I know, looked around for a few days for an answer...

The value error when FLOAT assigned the "line[4]", and the TypeError if I don't cast the variable.

I've also tried assigning them to new variables and casting the datatype. I think it is due to the rstrip() and strip() function output.