NuGet Gallery Feed for reblGreen.AI.JohnE5JohnE5 (based on everyone's favorite Short Circuit character) uses a weighted word association multi-category classifier concept which is ideal for training text taxonomization models. The project is open source and is designed to be an entry point into understanding the mechanics of machine learning. without mindblowing matrices. Using similar methods to Neive Bayes classification, JohnE5 takes a more linear approach to training, rather than the binary standard used in Neive Bayes. Read more about it in the GitHub repo.https://www.nuget.org/packages/reblGreen.AI.JohnE5/2019-11-27T15:09:53Zhttps://api.nuget.org/v3-flatcontainer/reblgreen.ai.johne5/1.0.0/iconhttps://www.nuget.org/packages/reblGreen.AI.JohnE5/1.0.0reblGreen.AI.JohnE5 1.0.02019-11-27T15:07:21Z2019-11-27T15:09:53Zreblgreenhttps://www.nuget.org/profiles/reblgreenJohnE5 (based on everyone's favorite Short Circuit character) uses a weighted word association multi-category classifier concept which is ideal for training text taxonomization models. The project is open source and is designed to be an entry point into understanding the mechanics of machine learning. without mindblowing matrices. Using similar methods to Neive Bayes classification, JohnE5 takes a more linear approach to training, rather than the binary standard used in Neive Bayes. Read more about it in the GitHub repo.