What are the different Algorithm techniques in Machine Learning?
A. supervised learning and semi-supervised learning
B. unsupervised learning and transduction
C. both A & B
D. none of the mentioned
Answer: Option A
Solution(By Examveda Team)What are the different algorithm techniques in Machine Learning?
Option A: Supervised Learning and Semi-Supervised Learning
Supervised learning involves training a machine learning model using labeled data, where the target variable is known. Semi-supervised learning combines both labeled and unlabeled data for training. These are indeed different algorithm techniques in machine learning, making Option A a correct choice.
Option B: Unsupervised Learning and Transduction
Unsupervised learning involves training models on unlabeled data to discover patterns or groupings in the data. Transduction, on the other hand, is not a commonly recognized machine learning technique. So, Option B is not the correct answer.
Option C: Both A & B
Both supervised learning (Option A) and unsupervised learning (part of Option B) are indeed different algorithm techniques in machine learning. However, transduction (the other part of Option B) is not commonly mentioned as a core machine learning technique. Therefore, Option C is not the correct answer.
Option D: None of the Mentioned
Since at least one of the options (Option A) represents different algorithm techniques in machine learning, Option D is not the correct answer.
In summary, the different algorithm techniques in machine learning include supervised learning and semi-supervised learning, as described in Option A.
D. all of the above
A. machine learning model
B. machine learning algorithm
A. data mining.
B. artificial intelligence
C. big data computing
D. internet of things