I thought about this task. We have enough examples where encoders are used as part of preprocessing and have regression or classification algorithm as a result. I suggest in this ticket to prepare example that are not ended with the trainer, please have a look to examples/ml/dataset folder Maybe you could create something meaningful like this.
Your choice! пт, 14 февр. 2020 г. в 10:17, Alexey Zinoviev <zaleslaw....@gmail.com>: > Hi, Lev! > I'll return with explanation on next week, maybe I need to adds some > details to this ticket. > > P.S. About dataset - you could search among the datasets presented in > MLSandbox class or could add your own (I'd prefer small datasets from > http://archive.ics.uci.edu/ml/index.php) > > > пт, 14 февр. 2020 г. в 10:02, Лев Киселев <lev.kiselev.1...@gmail.com>: > >> Hello everyone >> I'd like to take following task: >> >> https://issues.apache.org/jira/browse/IGNITE-12384?jql=project%20%3D%20IGNITE%20AND%20status%20in%20(Open%2C%20Reopened)%20AND%20component%20%3D%20ML%20AND%20labels%20%3D%20newbie >> >> But I do not fully understand what exactly needs to be done. >> As far as I understand encoders are needed to convert categorical >> variables >> to numerical. So, to demonstrate how they works I need some dataset with >> several categorical features. Should I search for it or generate by >> myself? >> Then, do I need to solve some regression/classification problem in order >> to demonstrate "power" of using categorical variables to fit prediction or >> classification models? >> >
