Table 3.1 shows the training data for predicting if a tumor is malignant or non- malignant based on tumor size. Table 3.1 Tumor Size (x) Malignant (y) 3 no 5 no 7 yes 9 yes Suppose logistic regression is used to perform tumor classification. Write down the hypothesis function hø(x) using parameters (0, 01) for the model. (i) = 0.5) and model B (0, =-1, 0, = 0.3), Given model A (0, = -3, 01 determine which model is a better fit for the training data in Table 3.1. Justify your answer by computing their respective classification accuracies. (ii) %3D %3D Suppose that gradient descent is used to train the model. Specify the update equation for logistic regression. (iii)
Table 3.1 shows the training data for predicting if a tumor is malignant or non- malignant based on tumor size. Table 3.1 Tumor Size (x) Malignant (y) 3 no 5 no 7 yes 9 yes Suppose logistic regression is used to perform tumor classification. Write down the hypothesis function hø(x) using parameters (0, 01) for the model. (i) = 0.5) and model B (0, =-1, 0, = 0.3), Given model A (0, = -3, 01 determine which model is a better fit for the training data in Table 3.1. Justify your answer by computing their respective classification accuracies. (ii) %3D %3D Suppose that gradient descent is used to train the model. Specify the update equation for logistic regression. (iii)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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