Logistic Regression Explained with Practical example
In this video, I have explained what is logistic regression, What is Sigmoid Function and S shaped curve. What is the math behind logistic regression and how to create own logistic regression algorithm.
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What is meant by logistic regression?
Logistic regression is a statistical analysis method used to predict a data value based on prior observations of a data set. A logistic regression model predicts a dependent data variable by analyzing the relationship between one or more existing independent variables.
What is the main purpose of logistic regression?
Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest.
Why logistic regression is the best?
Logistic regression is a simple and more efficient method for binary and linear classification problems. It is a classification model, which is very easy to realize and achieves very good performance with linearly separable classes. It is an extensively employed algorithm for classification in industry.
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