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==Explain Like I'm 5 (ELI5)==
==Explain Like I'm 5 (ELI5)==
Machine learning relies on computer programs to determine whether something is good or bad. If the program says something is bad and it turns out to be true, we call that a "true negative."
Machine learning often refers to a "true negative," such as when your mom inspects your room for messes and doesn't find any, even though you didn't make them.
 
Imagine your mom checking your room and saying, "Good job, there are no messes in here!" This would be a true negative as there was no mess made and she correctly identified that there weren't any in the room.
 
Machine learning teaches computers how to recognize things, like pictures of dogs. A true negative is when the computer correctly determines that something is not a dog when it actually is one.
 
So it's like the computer playing "find the dog", correctly saying "this picture is not a dog" when there is none present. This is good as we want the computer to be able to accurately identify when something isn't a dog.


[[Category:Terms]] [[Category:Machine learning terms]]
[[Category:Terms]] [[Category:Machine learning terms]]