Given below are two statements: one is labelled as Assertion A and the other is labelled as Reason R Assertion A: In supervised learning, the model is trained using labelled data. Reason R: Supervised learning algorithms find patterns in data to predict outcomes without any prior knowledge of the correct output. In the light of the above statements, choose the most appropriate answer from the options given below
Supervised Learning Assertion & Reason Analysis
Assertion A states that in supervised learning, the model is trained using labelled data.
This statement is correct. The fundamental characteristic of supervised learning is the use of a dataset where each input data point is associated with a known, correct output label. This labelled data guides the learning process.
Reason R claims that supervised learning algorithms find patterns in data to predict outcomes without any prior knowledge of the correct output.
This statement is incorrect. Supervised learning explicitly uses the 'correct output' (the labels) from the training data to learn the relationship between inputs and outputs. The goal is to minimize the difference between the model's predictions and these known correct outputs. Algorithms that work without prior knowledge of correct outputs are generally categorized as unsupervised learning.
Since Assertion A is factually correct about supervised learning and Reason R incorrectly describes its mechanism, the appropriate choice is that A is correct and R is not.
Important Questions from Artificial Intelligence - Teaching
- The term 'Artificial Intelligence' was coined by:
- Which planning approach is used for environment with no observations?
- In artificial intelligence, the term "Turing Test" is primarily associated with:
Given below are two statements: one is labelled as Assertion A and the other is labelled as Reason R
Assertion A: Unsupervised learning algorithms are used for tasks like data summarization and exploratory data analysis.
Reason R: Unsupervised learning requires labelled dataset to find relationships and patterns in data.
In the light of the above statements, choose the most appropriate answer from the options given below
Consider the following statements about reinforcement learning.
A. The adaptive dynamic programming agent leaves the transition model between states utilizes to solve the corresponding Markov decision process using dynamic programming.
B. Temporal difference needs a transition model to perform its updates.
C. The prioritized sweeping heuristic focuses on adjusting states with successors that have undergone significant changes in utility estimates.
D. The approach of modified policy iteration involves adopting a simplified value utility estimates following each change to the learned model.
Choose the correct answer from the options given below :
