Question

If training time can be traded for accuracy, we can use _____________. (wrt Azure ML)
1) Neural Networks
2) Decision Forest
3) Boosted Decision Tree
4) Logistic Regression

Answer 1

Answer:

3) Boosted Decision Tree

Explanation:

The answer to the question "What machine learning algorithm should I use?" is always "It depends." It depends on the size, quality, and nature of the data. It depends on what you want to do with the answer. It depends on how the math of the algorithm was translated into instructions for the computer you are using. And it depends on how much time you have. Even the most experienced data scientists can't tell which algorithm will perform best before trying them.

Answer 2

If the training time is traded for accuracy, boosted decision tree is used.

• Boosting decision tree means that each tree depends on the preceding trees. In a decision tree method, boosting tends to improve the overall accuracy with some small risk of less coverage.
• It is a regression method, and is a supervised method of learning, and therefore requires a data set which is labeled.
• Boosting builds a step wise tree series, and then selects an optimal tree through arbitrary differentiable loss function to generate accuracy.