!!! Overview
[{$pagename}] is the [model] of an [Artificial Neural network] 

[{$pagename}]s (and Statistics Models) the [Bias error]–[Variance error] tradeoff (or dilemma) is the problem of simultaneously minimizing two sources of [error] that prevent [Supervised Learning] [Mapping function] from generalizing beyond their [Training dataset]:
* [underfitting]
* [overfitting]

!! Recommended 
Solve high [Bias error] ([Underfitting]) first then high [Variance error] ([overfitting]).

!! More Information
There might be more information for this subject on one of the following:
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