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I am working on pattern recognition program using R/python. What would be the best way to compare two or more figures and identify/recognize the similar or duplicate figures based on pattern recognition?
There are lots of papers on the internet, we can try to get the idea how to extract and process feature in a fingerprint. For instance, http://www.cse.unr.edu/~bebis/CS790Q/PaperPresentations/MinutiaeDetection.pdf
Then you can use whatever classifier you want such as support vector machine.
If you need more idea you can visit http://dermatoglyphics.org/11-basic-patterns-of-fingerprint/ to generalize
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Is it doable to update my trained model (fbprophet) in order to surpass the dilemma of retraining the whole dataset every time?
Thanks for your help in Advance
I found a solution using the warm-start approach, here.
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I'm very new to learning manim and well python. However, I'm trying to learn it to make nice videos for my students. I'm attempting to create some tree diagrams in manim, but I can't seem to find much help. I tried getting manim to use tikz, but I'm having trouble with that as well. Is there a nice way to make tree diagrams straight in manim?
The best way is that you create a class yourself to generate the trees, it is not complicated if you know how to order elements with VGroup and program the unions between each Node, since it is a personal project you will have to develop it on your own, you can also check Manim's Discord to request help from the community, the link is in the official Manim repository.
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I'm preparing my dataset to be preprocessed before training with CNN model but i couldn't generate data from this type of file which contain several signals.
I recommend using the gdflib library. It'll allow you to process your .gdf files by organizing your data into nodes for further processing.
It would also help if you could please provide a minimal reproducible example of what you have tried.
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My data was modelled with a Cox-regression, using R, however I would like to use this model into a python GUI. As my knowledge of R is very limited. This way non-coders would be able to 'predict' survival rates based on our model.
What is the best way that I could use this model (combination of 3 different regressions) in python?
Do you want to predict values based on your estimates?
In this case you can just copy the R outputs into python and apply to
respective procedures.
Do you want the user to be able to run "your R regression pipeline" from within Python?
There are python libraries that help with that. I find this
source a useful start.
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It would be really helpful if someone can explain and give an example of how to apply machine learning algorithms using scikit-learn and python to images,sound or videos. I know how to apply it to csv file just want to learn how it can be extended for multimedia files.
Thankyou
There's a section in the sklearn documentation on feature extracting that focuses on working with images. There's also a section of the docs that talk about working with images, video and audio. I suggest you spend some time going through these sections and the rest of the documentation.
The MNIST dataset is a standard dataset of images of hand written digits that is used in a lot of examples so if you're searching google for examples "MNIST sklearn" will probably be helpful.