Today, I'll build some terms.
"Principle of Assumed Consistency":
When an assumption must be made, assume the unknown data remains consistent with the known data (e.g. if all known apples are red, then assume that all unknown apples are also red).
"Principle of Assumed Exceptions":
When an assumption must be made, assume the unknown data contains exceptions to trends in the known data (e.g. if all known birds fly, then assume that there are unknown birds which do not fly).
"Principle of Infinite Assumptions":
When an assumption can reasonably be made, make it (e.g. if all known dogs have tails, then assume that all unkown dogs also have tails, and that all dogs wag their tails, and that all dogs curl their tails up to poop, and that all animals without tails are not dogs).
"Principle of Unassuming Data":
Assumptions cannot be made, only hard data is known (e.g. if all known toads hop, then assume nothing about unknown toads).
