search

ChristophRaab / rrslvq

Code release of Reactive Robust Learning Vector Quantization
https://www.sciencedirect.com/science/article/abs/pii/S0925231220305063
MIT License
5 stars 1 forks source link

Running `study_perfomance_detectors.py` raises `ModuleNotFoundError` #6

Open yuritpinheiro opened 3 years ago

yuritpinheiro commented 3 years ago

I'm trying to run the study_perfomance_detectors.py but the error ModuleNotFoundError is raised due the file cd_naive_bayes.py not being in the study folder.

I wondering how you run this code. I know that if I move the files from one folder to another I can solve the error, but if there is a simpler and/or cleaner way to solve I would like to learn.

yuritpinheiro commented 3 years ago

I was also unable to identify where you reset the cls list for each stream.

yuritpinheiro commented 3 years ago

I ran the script study_perfomance_detectors.py moving the file cd_naive_bayes.py into the study folder.

I was thinking that you "dont need" to reset each classifier because scikit-multiflow uses a dict format for data and enables changes in data dimension. My code does not support and was crashing due to me using numpy arrays.

ChristophRaab commented 3 years ago

Hey @yuritpinheiro

thank you for reaching out to me. Your first issue could also be solved by setting the python path sys.path.append(your_path) or in your IDE. However, it made a commit which makes your life easier and adding some of the helper files to the repo.

Comment 2: The second issue is in fact a copy past mistake, i made a new commit with the bug fix. However, i am not sure if this is a problem, because the concept drift detector will descard the naive bayes model immediatly after a new stream starts due to concept drift :)

Comment 3: I am not aware of resets of classifiers if you handle the stream by yourself - i don't think so but see #2. I am not sure why your code crashes with numpy arrays. In the study_performance_detectors.py the detectors receive numpy arrrays, too.

Can you provide more details?

Best Christoph

yuritpinheiro commented 3 years ago

Firstly, thank you your attention. I do appreciate the modifications for improving usage.

For importing cdnb, I thought you did something like it.

In my second comment, I missed line 30 in study/cd_naive_bayes.py. Now I see how the detectors are reset When changing the stream. Although, the zip() in line also in study/cd_naive_bayes.py maybe behaving in a unexpected fashion and slightly affect the startup at each new stream. A minor detail.

When I mentioned reset a classifier, I really meant the detector, so it already cleared.

Finnaly, I intend to create a n-dimensional concept drift detector. So the detector stores n-dimensional arrays based on the current stream. If the new stream has a different dimension, the operations will fail.

An example would be a sum of vectors. After processing some samples of a data 3 dimensional stream, my detector have a 3 dimensional vector store. When a new stream starts, if it has, e.g., 5 dimensions numpy will raise an error that I cant add a 3d vector (data stored in the detector) with 5d vector (sample of a new stream).

It is not an issue in your code. It is something that my code must comply.

Again, thank you for your attention!