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I know what Explanatory data analysis is and how it helps us investigate and understand the data. What I dont understand is how does this help in case of nonlinear relationships? I mean if I'm using neural nets for nonlinear regression for example, how will a heatmap help me understand my data since it gives only linear correlation and that doesn't matter because the data can have some nonlinear relationship that can't be seen with heatmaps or some other plots.

I think if we are using linear regression, EDA ist very usefull to understand and know which features are better than others etc.. but how does it help for nonlinear models?

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