Artificial Intelligence & Machine Learning
What is the function or purpose of Overfitting?
Difficulty: Hard
About this MCQ
This Hard Artificial Intelligence & Machine Learning MCQ checks one syllabus fact.
The question is: “What is the function or purpose of Overfitting?”
The accepted answer is B. A modeling error where a model learns the training data too well, including noise, and performs poorly on new data.. A modeling error where a model learns the training data too well including noise and performs poorly on new data is the fact required by What is the function or purpose of Overfitting option B Option A A subset of machine learning that uses neural networks with many layers to model complex patterns does not match the stem it is a near-miss used to catch incomplete recall of A modeling error where a model learns the training data too well including noise and performs poorly on new data Option C A supervised learning task that predicts a continuous numerical value does not match the stem it is a near-miss used to catch incomplete recall of A modeling error where a.
- A. A subset of machine learning that uses neural networks with many layers to model complex patterns.
Why not A: “A subset of machine learning that uses neural networks with many layers to model complex patterns.” is not correct. The accepted answer is B. A modeling error where a model learns the training data too well, including noise, and performs poorly on new data.. A modeling error where a model learns the training data too well including noise and performs poorly on new data is the fact required by What is the function or purpose of Overfitt
- B. A modeling error where a model learns the training data too well, including noise, and performs poorly on new data. ✓
- C. A supervised learning task that predicts a continuous numerical value.
Why not C: “A supervised learning task that predicts a continuous numerical value.” is not correct. The accepted answer is B. A modeling error where a model learns the training data too well, including noise, and performs poorly on new data.. A modeling error where a model learns the training data too well including noise and performs poorly on new data is the fact required by What is the function or purpose of Overfitt
- D. An optimization algorithm used to minimize a model's error by iteratively adjusting its parameters.
Why not D: “An optimization algorithm used to minimize a model's error by iteratively adjusting its parameters.” is not correct. The accepted answer is B. A modeling error where a model learns the training data too well, including noise, and performs poorly on new data.. A modeling error where a model learns the training data too well including noise and performs poorly on new data is the fact required by What is the function or purpose of Overfitt
Correct answer
B. A modeling error where a model learns the training data too well, including noise, and performs poorly on new data.
Explanation
A modeling error where a model learns the training data too well including noise and performs poorly on new data is the fact required by What is the function or purpose of Overfitting option B Option A A subset of machine learning that uses neural networks with many layers to model complex patterns does not match the stem it is a near-miss used to catch incomplete recall of A modeling error where a model learns the training data too well including noise and performs poorly on new data Option C A supervised learning task that predicts a continuous numerical value does not match the stem it is a near-miss used to catch incomplete recall of A modeling error where a.
Source: Artificial Intelligence & Machine Learning Official Reference Guide
Tags: computer science, AI, machine learning, data science
Submitted by: MCQsHub Editorial
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