MACHINE LEARNING
106403Unit 1: Introduction
Q1a. Which of the following is an example of supervised learning? (i) K-means clustering (ii) Linear regression (iii) PCA (iv) DBSCAN20252m
Unit 1: Introduction
View this question on its own page →Which of the following is an example of supervised learning?
(i) K-means clustering
(ii) Linear regression
(iii) PCA
(iv) DBSCANQ1b. The training dataset has 5 samples with predicted outputs [2,3,5,4,6] and actual outputs [3,3,4,5,6]. What is the Mean Squared Error (MSE)? (i) 0.2 (ii) 0.4 (iii) 0.5 (iv) 0.620252m
Unit 1: Introduction
View this question on its own page →The training dataset has 5 samples with predicted outputs [2,3,5,4,6] and actual outputs [3,3,4,5,6]. What is the Mean Squared Error (MSE)?
(i) 0.2
(ii) 0.4
(iii) 0.5
(iv) 0.6Q2a. Define machine learning. Compare and contrast the different types of learning. Include examples and explain the scenarios where each is best applied.20257m
Unit 1: Introduction
View this question on its own page →Define machine learning. Compare and contrast the different types of learning. Include examples and explain the scenarios where each is best applied.
Q2b. Describe the evaluation metrics used in machine learning, such as accuracy, precision, recall, and F1-score, with a numerical example. Explain the importance of cross-validation in estimating a model's generalization performance.20257m
Unit 1: Introduction
View this question on its own page →Describe the evaluation metrics used in machine learning, such as accuracy, precision, recall, and F1-score, with a numerical example. Explain the importance of cross-validation in estimating a model's generalization performance.
Q8a. Suppose 10000 patients are tested for flu; out of them, 9000 are actually healthy and 1000 are actually sick. For the sick people, a test was positive for 620 and negative for 380. For the healthy people, the same test was positive for 180 and negative for 8820. Construct a confusion matrix.20254m
Unit 1: Introduction
View this question on its own page →Suppose 10000 patients are tested for flu; out of them, 9000 are actually healthy and 1000 are actually sick. For the sick people, a test was positive for 620 and negative for 380. For the healthy people, the same test was positive for 180 and negative for 8820. Construct a confusion matrix.
Q9d. Write short note on: Hypothesis Space and Inductive Bias20257m
Unit 1: Introduction
View this question on its own page →Write short note on: Hypothesis Space and Inductive Bias