University : University of Bath UniLearnO is not sponsored or endorsed by this college or university.
Subject Code : M4MBA3
Country : United Kingdom
Assignment Task

 

1. Background:

Logistic Regression (LR) – also known as Logit Regression or Logit Model - is a statistical estimation method. Given a set of data, which classifies each data point in a binary manner, the aim is to find an exponential that can learn the patterns and return probabilities about future patterns.

As an example, assume that you are given a set of data about students that consists of if they have passed the MN50642 Optimisation unit (, with 0 meaning fail and 1 meaning pass), and how much time they have spent reading the textbook (), solving examples on paper (), and solving problems on a computer ().
LR makes use of the Logistic Function , a well-behaved function with useful mathematical properties, plotted in the figure below. Simply put, the Logistic Function is a continuous approximation of a step-function, better known as an if function. It has widespread uses in Machine Learning.

 

the Logistic Function;

 

The Logistic Function can be used as an estimator of the probability of an event since it returns values between 0 and 1. However, it is based only on one input, . We would like to find a linear function to replace the in the Logistic Function, of the form . The modified Logistic Function then can be used to estimate the probability that student will pass. Consequently, is the estimated probability that student will fail.

 

 

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  • Posted on : March 09th, 2019
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