Sigmoid
Logistic Regression, R, Regression

Implementing Logistic Regression using Titanic dataset in R

Introduction In my last post, “Understanding mathematics behind Logistic Regression“, I explained the basic maths behind logistic regression. In this post, I intend to implement logistic regression model in R using Titanic dataset. I have used Titanic dataset for explaining logistic regression where the target variable is ‘Survived’ which has two values 0 and 1. Data Dictionary Variable Definition Key…

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Basics, Regression

Understanding mathematics behind Logistic Regression

Introduction to Logistic Regression Logistic Regression is a type of regression in which returns the probability of occurrence of an event by fitting the data to a mathematical function called ‘logit function’. It is basically a classification algorithm and is used mostly when the dependent variable is categorical, the independent variables can be discrete or continuous. Generalized Linear Models Before starting with…

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final eqn.
R, Regression

Understanding Softmax Regression with an example in R

Introduction to Softmax Regression We have commonly used many classification algorithms for binary classification. Now we will see a classification technique which is used to classify k classes. This technique is called softmax regression. Softmax regression is also called as multinomial logistic regression and it is a generalization of logistic regression. Softmax regression is used to model categorical dependent variables…

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Regression

Locally Weighted Regression (LWL)

Locally Weighted Regression (LWL) or LOWESS The basic assumption for a linear regression is that the data must be linearly distributed. But what if the data is not linearly distributed. Can we still apply the idea of regression? And the answer is ‘yes’… we can apply regression and it is called as locally weighted regression. We can apply LOESS or…

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Basics, Linear Regression, Regression

Linear Regression in R and its interpretation

Linear Regression Linear regression modeling is one of the most frequently used supervised learning technique. It is useful when the dependent variable is continuous (ratio or interval scale) and there exists a linear relationship between the dependent and independent variables. This post is a quick guide to perform linear regression in R and how to interpret the model results. In the…

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