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Symbolic regression is a method for finding equations that relate variables.
It has been used in research in physics, chemistry, biology, and engineering.
Key novel methods and modern programs can be used to perform symbolic regression.
Symbolic regression has various real-world applications.
Key Features:
Symbolic regression finds equations that relate variables.
It has had an impact on research in various scientific fields.
There are novel methods and programs available for performing symbolic regression.
Symbolic regression can be applied to real-world problems in physics, chemistry, biology, and engineering.
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