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You're reading from  R Bioinformatics Cookbook - Second Edition

Product typeBook
Published inOct 2023
PublisherPackt
ISBN-139781837634279
Edition2nd Edition
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Dan MacLean
Dan MacLean
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Dan MacLean

Professor Dan MacLean has a PhD in molecular biology from the University of Cambridge and gained postdoctoral experience in genomics and bioinformatics at Stanford University in California. Dan is now an honorary professor at the School of Computing Sciences at the University of East Anglia. He has worked in bioinformatics and plant pathogenomics, specializing in R and Bioconductor, and has developed analytical workflows in bioinformatics, genomics, genetics, image analysis, and proteomics at the Sainsbury Laboratory since 2006. Dan has developed and published software packages in R, Ruby, and Python, with over 100,000 downloads combined.
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Using logistic regression to classify the relative likelihood of two outcomes

Logistic regression is a statistical modeling technique used to predict categorical outcomes, particularly in binary classification situations where the outcome can take one of two possible values. It aims to find the relationship between a set of input variables and the probability of a certain outcome occurring. Logistic regression estimates the relationship between these input variables and the probability of the outcome. It tries to find the best-fit line or curve that represents this relationship. Unlike linear regression, which predicts continuous values, logistic regression predicts the probability of a specific outcome. We set a probability threshold (usually 0.5) to decide the class label. If the predicted probability is above the threshold, the outcome is predicted as one class, and if it is below the threshold, the outcome is predicted as the other class. Once the model is trained, it can be used...

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R Bioinformatics Cookbook - Second Edition
Published in: Oct 2023Publisher: PacktISBN-13: 9781837634279

Author (1)

author image
Dan MacLean

Professor Dan MacLean has a PhD in molecular biology from the University of Cambridge and gained postdoctoral experience in genomics and bioinformatics at Stanford University in California. Dan is now an honorary professor at the School of Computing Sciences at the University of East Anglia. He has worked in bioinformatics and plant pathogenomics, specializing in R and Bioconductor, and has developed analytical workflows in bioinformatics, genomics, genetics, image analysis, and proteomics at the Sainsbury Laboratory since 2006. Dan has developed and published software packages in R, Ruby, and Python, with over 100,000 downloads combined.
Read more about Dan MacLean