AdaBoost, Clearly Explained
Key words and equation
- Stump(树桩) means classification just by one feature
- Amount of say
$$
\text{Amout of say} = \frac{1}{2}\log{(\frac{1-\text{Total Error}}{\text{Total Error}})}
$$
- Wrong Classified Sample New Weight
$$
\text{New Sample Weight} = \text{Sample Weight}\times e^{\text{amount of say}}
$$
- Correct Clasified Sample New Weight
$$
\text{New Sample Weight} = \text{Sample Weight}\times e^{-\text{amount of say}}
$$
- After reassing sample weight, do bootstrap sample based on their new weight, it will select big weight sample lots of times to adjust next model
- In last prediction, the amount of say decide which results we will pick.
Question