December 2016
Beginner to intermediate
392 pages
8h 13m
English
Content preview from Apache Spark for Data Science CookbookBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Applying logistic regression on bank marketing data
Logistic regression is a classification algorithm. It is used to predict a binary outcome (0/1, Yes/No, True/False) from the set of independent variables. It is a special case of linear regression where the outcome variable is categorical. The log of odds is the dependent variables, that is, it predicts the probability of occurrence of an event by fitting data to a logit function. Logistic regression is also termed as linear classification model. The link function used in the logistic regression is the logic link 1/(1+exp(-wTx)). The related loss function for logistic regression is the logistic loss, that is, log(1+exp(-ywTx)). Here y is the actual target variable (either 1 for the positive class ...
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