3 Mg, 0 Fe2O3, 3MgO, 2 Fe
Correct option:
Entropy is used to calculate information gain.
What is entropy?
- Entropy is the measure of data's uncertainty or randomness; the greater the randomness, the higher the entropy. Entropy is used by information gain to make choices. Information will increase if the entropy decreases.
- Decision trees and random forests leverage information gained to determine the appropriate split. Therefore, the split will be better and the entropy will lower the more information gained.
- Information gain is calculated by comparing the entropy of a dataset before and after a split.
- Entropy is a way to quantify data uncertainty. The goal is to maximize information gain while minimizing entropy. The method prioritizes the feature with the most information, which is utilized to train the model.
- Entropy is actually used when you use information gain.
Learn more about entropy here,
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This is called adaptation. An example would be a polar bear with white fur. They have this to be more efficent hunters, as they use it as a type of camouflage in order to sneak up on prey. Brown bear use this in the same way but their environment requires them to be brown in order to blend in beter with trees. So basicly adaptation
Answer:
100 °C, because it is the boiling point of water.
Explanation:
