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Clarify regression to a non-technical viewers with residual, weight, impact and SHAP plots
“And don’t use any math” was my supervisor’s instruction.
How else am I supposed to clarify how regression works!?
Little did I do know {that a} massive a part of an information scientist’s job is to clarify fashions in non-technical phrases. All we have to perceive a linear mannequin is a regression abstract. However this desk of numbers will rapidly bore (or frighten) a distinct viewers. To get your level throughout, you’ll want to make use of extra digestible visualisations. So, we’ll discover 8 plots that can enable you to make linear regression extra accessible:
- Residual plots
- Correlation heatmaps
- Weight plots
- Impact plot
- Imply impact plot
- Particular person impact plot
- Pattern impact plot
- SHAP values for linear fashions
We’ll see that plots 4 to 7 are significantly helpful as they assist clarify a mannequin by way of its contribution to a prediction. We “reframe” the outcomes by way of a amount that everybody understands. For instance, we will go from explaining regression parameters to…
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