5. Write a function logisticClassify that takes in the m feature values for the n data points as a np-array with dimensions (n,m) and the weight vector w as a np-array with dimension (m+1) (with b as the final element of w). The function returns the 0/1 label for each data point as a np-array of dimension (n). Use the following syntax: classLabels=logisticClassify(x,w)

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
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Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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5. Write a function logisticClassify that takes in the m feature values for the n data points as a
np-array with dimensions (n,m) and the weight vector w as a np-array with dimension (m+1)
(with b as the final element of w). The function returns the 0/1 label for each data point as a
np-array of dimension (n).
Use the following syntax:
classLabels=logisticClassify(x,w)
Transcribed Image Text:5. Write a function logisticClassify that takes in the m feature values for the n data points as a np-array with dimensions (n,m) and the weight vector w as a np-array with dimension (m+1) (with b as the final element of w). The function returns the 0/1 label for each data point as a np-array of dimension (n). Use the following syntax: classLabels=logisticClassify(x,w)
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