One-Hot Encoding

Example

• I like NLP
• I like DL
• DL is AI

단어	One-Hot Vector
I	[1 0 0 0 0 0]
like	[0 1 0 0 0 0]
NLP	[0 0 1 0 0 0]
DL	[0 0 0 1 0 0]
is	[0 0 0 0 1 0]
AI	[0 0 0 0 0 1]

왜 1, 2, 3, 4로 인덱싱하지 않고 One-Hot Encoding 을 사용하는가?

ex) MSE as the cost function
$Lostfunction=\frac{1}{n}{\sum }_i^n(y_i-{\hat{y}}_i{)}^2$

Banana	Tomato	Apple
1	2	3
Answer: Tomato(2)
Prediction: Banana(1)
**MSE:1

Answer: Apple(3)
Prediction: Banana(1)
**MSE: 4

토마토-바나나가 사과-바나나보다 유사한가? → 아니기 때문에
벡터로 표현해야 한다!