Answer:
c. Performs better on training data as the training process proceeds, while performing worse on a held-out test data
Explanation:
An over-fitted model is one that will perform best on training but would fail or do worse on a held-out test data.
Such models are optimum for a just a particular set of data but would grossly failed when extrapolated to some other data set not novel to it.
- Over-fitting a model implies that a model closely corresponds to a set of data but would not perform well with others.
- It is usually as a result of a model adapting the noise and other details of a particular data set and thereby incorporates it.
- This makes it difficult for the model to fit into another data set.
Answer:
D.Elastic energy| Magentic energy
Hello
You expect to see:
1) A solar eclipse, when the earth is between the sun and the moon: the shadow of the earth is projected on the moon surface, and the sun will appear dark
2) An "earth eclipse", when the moon is between the sun and the earth: the shadow of the moon is projected on the earth surface, therefore the earth will appear dark.