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"Garbage in, garbage out" means...
if the inputs to a computational process are incorrect, then the outputs from the process will be incorrect.
if the analyst makes programming errors, no solution can be computed.
if the Garbage function of a machine learning algorithm is not properly configured, then the outputs will only show known data correlations.
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