Machine Learning - Steps to Build Regression Model

A number of real life business decisions are of a regression in nature. We have prepared a  detailed list of regression modelling scenarios. Business Scenario: House Price Prediction We all want to have our own house and price of a house is a imprtant link betewen our wish and owning a house. We want to build ... Read moreMachine Learning - Steps to Build Regression Model

Estimating Regression Beta Coefficients using Matrix Calculation

In our series of blogs on Multiple Regression, we have already shared details on following and now focus is to show Beta Coefficient Estimation using Matrix Calculations in R. Multiple Regression Application Scenarios Multiple Regression Tutorial Multi-collinearity Assumption Normality Assumption Step by Steps Explanation of Beta Coefficient Estimation in Multiple Regression Reading Data # Sample ... Read moreEstimating Regression Beta Coefficients using Matrix Calculation

Multiple Regression Model Tutorial

When do you use Multiple Regression? Based on scale of measurement, variables can be defined as Binary, Ordinal, Nominal and Continuous (Ratio and Interval Scale) type. When a decision (or target/dependent) variable is continuous, one of the Statistical Methods available for building the model is multiple regression.  These type of scenarios or problems are classified ... Read moreMultiple Regression Model Tutorial

Multiple Regression: Normality Assumption

There are a few assumptions involved in Multiple Regression and one of these assumption is Normality assumption. Some of the other assumptions discussed in other blogs - Linearity, Multi-collinearity and Hopescadasticity. This assumption is probably least important.  Parameter Estimation Method – Ordinary Least Square (OLS) – is not dependent on this assumption. In my view, it ... Read moreMultiple Regression: Normality Assumption

Scenarios: Multiple Regression Applications

Key criteria used to check whether multiple regression technique can be used is continuous target or dependent variable. Some of the scenarios and ideas are list below. These examples are across functional areas and business verticals.   Industry Vertical Scenario Scenario Description   Human Resource Salary Estimate Predicting or estimating salary of a person based ... Read moreScenarios: Multiple Regression Applications

Assumptions of Linear Regression or Multiple Regression – Explained

Each of the Statistical Techniques has some underlying assumptions. Multiple Regression has a few and we will explain and illustrate those using examples. Multiple Regression Approach A tutorial on Multiple Regression Examples of Multiple Regression Applications Multiple Regression using an analytics tool – SAS /R Some fundamental assumptions Linear relationship Multivariate normality No or little ... Read moreAssumptions of Linear Regression or Multiple Regression – Explained

Bagging for Regression using R

In the previous blog, we had discussed on how Bagging works and also explained application for a classification scenario. Bagging can be applied for Regression Decision Tree and regression problem. In the regression scenario, the target/decision variable is a continuous variable. Scenario: Cash Collection Forecasting In a business scenario, the objective is to forecast value ... Read moreBagging for Regression using R