Logistic regression

What is logistic regression?
Logistic regression is a type of statistical analysis used to predict the outcome of a dependent variable based on previous observations. For example, an algorithm could determine the winner of a presidential election based on past election results and economic data. Logistic regression algorithms are popular in machine learning.

Logistic regression is a technique in statistical analysis that attempts to predict a data value based on previous observations. A logistic regression algorithm looks at the relationship between a dependent variable and one or more dependent variables.

Logistic regression has a number of uses in machine learning. A logistic regression algorithm could attempt to predict which candidate would win an election by averaging all query results. A more sophisticated algorithm could also include economic data and past elections in its model. Another algorithm could try to find out which users on a website click on certain ads. It is also widely used in database preparation to classify data for extract, transform and load (ETL) operations.

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