Comments (3)
Hi @cesarsouza,
Thanks for letting me know. I am a bit sad to see Accord.Net archived, but I defenitely understand that priorities can shift, and that it can be hard to keep up. I have many things I would like to develop for SharpLearning also, but sadly spare time is not unlimited :).
Many thanks for letting me know about the licenses and algorithms, I will defenitely check that out, and let you know if I start adapting some of them for SharpLearning.
Also, a big thanks for your immense work on the Accord.NET framework for all those years. I am sure you learnt a ton of things during that period. I hope you will continue to be active in the open source community!
All the best and I hope you had a merry (and corona free) Christmas.
Happy new year also!
Best regards
Mads
from sharplearning.
Hi @mdabros,
I wish you also had an amazing (and Corona free) Christmas as well and I wish you an even better new years!
Yes I did learn quite a lot, and there were so many things in my life that happened just because I had started that project. But now it's time to look towards the future! And by that, I mean, supporting people who have also aimed for similar goals I once had. I am quite sure the SharpLearning project has also brought you new knowledge and new perspectives, and I hope it will continue to do so!
Regards,
Cesar
from sharplearning.
For example, I've seen that SharpLearning doesn't have support for meta-learning algorithms such as RANSAC or some convex optimization algorithms such as SVMs and/or some other fancy algorithms for logistic regression. If you would ever like to add them to your framework, please feel free to check out the Accord source code and copy-and-paste/re-implement them as you like. If I am the sole developer (as noted in the header of each file), I would be more than willing to grant you rights to do so under any of the super permissible licenses such as the MIT license. If I am not the only developer, I actually have a list of contributors who had agreed to also license their work into the MIT and, if there is a file where I was not the sole author but where you would like to base your code upon, I can give you proofs that you would be allowed to do so.
IMHO you've done absolutely right to have started this project under the MIT instead of one of the (L)GPL licenses. If there is anything I could help with, please let me know!
Cheers,
Cesar
from sharplearning.
Related Issues (20)
- Add parallelism to Bayesian Optimizer. Also allow resampling non-deterministic algorithms HOT 2
- TrimSplitLineTrimColumnsToDictionary throws a "key already exists" exception HOT 1
- Issue with loading model using GenericXmlDataContractSerializer: The deserializer has no knowledge of any type that maps to this name HOT 4
- Order of results from RandomSearch is not deterministic with different iteration counts. HOT 1
- Is there a way to keep textual labels / targets as a part of the trained model? HOT 5
- Serialization Exception HOT 2
- Continuously improving a neural network over time using small batches. HOT 1
- SharpLearning.XGBoost.dll is not compatible with .net core HOT 6
- Exception when serializing neural net to XML HOT 2
- A way to Save Bayesian Optimizer progress and continue later. HOT 1
- Access OOB data and OOB error calculations of Random Forest HOT 2
- how can i train the Neural Network with my own Training Pictures? HOT 1
- HPO wiki page
- How can I be able to learn with your repository HOT 3
- Looking for an example for loading from a Stream source HOT 4
- Error in getting started code example HOT 1
- Unhandled Exception: System.Runtime.Serialization.SerializationException: The internal array cannot expand to greater than Int32.MaxValue elements. HOT 1
- SharpLearning can only load models trained in python with xgboost==0.82 HOT 1
- Monitoring training progress HOT 1
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from sharplearning.