You're reading from Interpretable Machine Learning with Python - Second Edition

Product typeBook

Published inOct 2023

PublisherPackt

ISBN-139781803235424

Edition2nd Edition

Concepts

Machine Learning

Author (1)

Serg Masís

The approach

Logistic regression is one common way to rank risk factors in medical use cases. Unlike linear regression, it doesn’t try to predict a continuous value for each of our observations, but it predicts a probability score that an observation belongs to a particular class. In this case, what we are trying to predict is, given x data for each patient, what is the y probability, from 0 to 1, that they have CVD?

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Interpretable Machine Learning with Python - Second Edition

Published in: Oct 2023Publisher: PacktISBN-13: 9781803235424

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Author (1)

Serg Masís

Serg Masís has been at the confluence of the internet, application development, and analytics for the last two decades. Currently, he's a climate and agronomic data scientist at Syngenta, a leading agribusiness company with a mission to improve global food security. Before that role, he co-founded a start-up, incubated by Harvard Innovation Labs, that combined the power of cloud computing and machine learning with principles in decision-making science to expose users to new places and events. Whether it pertains to leisure activities, plant diseases, or customer lifetime value, Serg is passionate about providing the often-missing link between data and decision-making—and machine learning interpretation helps bridge this gap robustly.
Read more about Serg Masís

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