I think Optical Drive does.
Answer:
I think the answer is option D (double-click Format Painter)
Explanation:
Answer:
The various reasons that could be a major problem for the implementation are it involves a large number of parameters also, having a noisy data
Explanation:
Solution
The various reasons that could be causing the problem is given as follows :
1. A wide number of parameters :
-
In the ensemble tree method, the number of parameters which are needed to be trained is very large in numbers.
- When the training is performed in this tree, then the model files the data too well.
- When the model has tested against the new data point form the validation set, then this causes a large error because the model is trained completely according to the training data.
2. Noisy Data:
- The data used to train the model is taken from the real world . The real world's data set is often noisy i.e. contains the missing filed or the wrong values.
- When the tree is trained on this noisy data, then it sets its parameters according to the training data.
- As regards to testing the model by applying the validate set, the model gives a large error of high in accuracy
y.
The answer is incremental backup as this is the one
responsible of having to provide a backup with files that are modified since
the last backup it has received, it is considered to be a backup in which is a
type of security copy.
