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Porting real-world ML model(s) into ZK #3
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Dear Dr. Cathie @socathie and Paul @NOOMA-42 , I hope to work on this task. My idea now is to predict the probability distribution of hourly rainfall from polarimetric radar measurements. The use of radar to assess rainfall is widely used in agricultural production. Currently prevalent models include decision trees, random forests, and XGBoost. Proven assessment results can be combined with on-chain Oracle to enrich the data sources for on-chain decision-making. I think it's a scenario that makes practical sense, and the model is relatively mild in complexity, making it more conducive to implementation on a laptop. I am wondering your opinions on this idea and look forward to your comments. Have a nice day! Best regards, |
Hi Li, sorry for missing out your question. Having XGBoost will be really helpful. This sounds to me very valid. Would you be able to submit a proposal?
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Hi Paul. Thank you very much for your kind answer! I am thrilled you like the idea. I will make a proposal to give more explanation for the idea and the plan. I am very excited to have a chance to work with the PSE team and look forward to receiving your comments. Best wishes, |
Open Task RFP for Porting real-world ML model(s) into ZK
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