Showing entries tagged [regression]

Quick Tips for ESS Machine Learning Projects

Your idea of what's entailed in setting up a supervised Machine Learning (ML) project as an Earth Systems scientist is probably not as fanciful as what an image generation algorithm came up with. But there are many little decisions ML practitioners make along the way when starting an Earth Systems Science (ESS) ML project. This article provides some tips and ideas to consider as you're getting started. These tips are not in any particular order, and like all things related to ML projects they depend on the specific types of data and project goals.

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R2: Downsides and Potential Pitfalls for ESS ML Prediction

Datasaurus plot
Always plot your data!

Regression analysis is a fundamental concept in the field of machine learning (ML), in that it helps establish relationships among the variables by estimating how one variable affects the other.

The coefficient of determination, R2 (pronounced “R squared”), is a measure that provides information about how well the regression line suggested by a numerical model approximates the actual data (often referred to as “goodness of fit”).

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News and information from the Unidata Program Center

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