Robotics & Machine Learning Daily News2024,Issue(Aug.7) :18-19.

Report Summarizes Machine Learning Study Findings from U.S. GeologicalSurvey (U SGS) (A Spatial Machine Learning Model Developed From Noisy Data Requires Multis cale Performance Evaluation: Predicting Depth To Bedrock In the Delaware River . ..)

Robotics & Machine Learning Daily News2024,Issue(Aug.7) :18-19.

Report Summarizes Machine Learning Study Findings from U.S. GeologicalSurvey (U SGS) (A Spatial Machine Learning Model Developed From Noisy Data Requires Multis cale Performance Evaluation: Predicting Depth To Bedrock In the Delaware River . ..)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Fresh data on Machine Learning are pre sented in a new report. According to newsreporting from Catonsville, Maryland, by NewsRx journalists, research stated, “Spatial machine learningmodels can be developed from observations with substantial unexplainable variability, sometime s called‘noise ‘. Traditional point-scale metrics (e.g., R 2 ) alone can be mis leading when evaluating these models.We present a multi-scale performance evalu ation (MPE) using two additional scales (distributional andgeostatistical).”

Key words

Catonsville/Maryland/United States/No rth and Central America/Cyborgs/Emerging Technologies/Machine Learning/U.S. Geological Survey (USGS)

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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