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# Logistic Regression

• January 14, 2023
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### Meet the Author : Mr. Bharani Kumar

Bharani Kumar Depuru is a well known IT personality from Hyderabad. He is the Founder and Director of Innodatatics Pvt Ltd and 360DigiTMG. Bharani Kumar is an IIT and ISB alumni with more than 18+ years of experience, he held prominent positions in the IT elites like HSBC, ITC Infotech, Infosys, and Deloitte. He is a prevalent IT consultant specializing in Industrial Revolution 4.0 implementation, Data Analytics practice setup, Artificial Intelligence, Big Data Analytics, Industrial IoT, Business Intelligence and Business Management. Bharani Kumar is also the chief trainer at 360DigiTMG with more than Ten years of experience and has been making the IT transition journey easy for his students. 360DigiTMG is at the forefront of delivering quality education, thereby bridging the gap between academia and industry.

Predicts the probability of the outcome class.

The algorithm finds the linear relationship between independent variables and a link function of these probabilities.

The link function that provides the best goodness-of-fit for the given data is chosen.

The output from logistic regression will lie between 0 to 1.

The logistic regression curve is known as Sigmoid Curve.

Probability values are segregated into binary outcomes using a Cutoff value. The default cutoff is treated as 0.5 (50%)

• If probability of an event > 0.5; then Event is considered to be True (predicted outcome = 1)
• If probability of an event

The logistic regression performed using:

Where,

β0 = the y-axis intercept

βi = the model coefficient for the linear effect of variable is on y

e = the random error

##### The probability function:

The output of the logistic regression will give a sigmoid curve (also known as S curve)

Interpretation: Probability p indicates that the event has a chance ‘p’ for a given input ‘x’.

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