Basics, Neural Networks, Python

Using K-means to find the optimal nodal center for Radial Basis Function

 Introduction In my previous article on “Introduction to the perceptron algorithm”  we had seen how a single layer perceptron model can be used to classify an OR gate. But when the same model was used to classify a XOR gate it failed miserably. The problem was with linearity, i.e. if the classes are not linearly separable “Single layer perceptron model”…

Continue Reading

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…

Continue Reading


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…

Continue Reading

Time Series Forecasting

“Correlogram Analysis” Finding the order of Mean model in Time Series Analysis

Introduction to Corellogram Analysis To all those who know how to model a Time Series data using ARIMA ,you must have come across the term “Correlogram Analysis“,and to all those who don’t know what it is let me start with a basic definition. In the analysis of data, a correlogram is an image of correlation statistics. In time series analysis, a correlogram, also known as an autocorrelation…

Continue Reading

R, Visualization Tutorials

Plotting maps in R using ggmap

Introduction The objective is to explore ‘ggmap’ package in R and use this package to plot points on the map. Also, you can view other posts related to visualizations here. For this post, I’ll be using the map of India. Initially, I’ll try to explain some of the basic functions in ggmap and then I’ll explain by plotting different airports…

Continue Reading

Basics, Deep Learning, Neural Networks, Python

Introduction to the Perceptron Algorithm

Perceptron Algorithm The Perceptron model forms the basis of any neural network. This is where it all began and finally led to the development of “Neural Networks” or “Deep Learning” which is kind of the buzz word nowadays. In this article, I am going to show the mathematics behind the well-known Perceptron algorithm using a 2-input 2-output model. Although some amount of linear algebra…

Continue Reading

Data Envelopment Analysis, Optimization, R

Introduction to Data Envelopment Analysis in R

Introduction to Data Envelopment Analysis Data Envelopment Analysis is a Performance Measurement technique which is used for comparing the performances of similar units of an organization. The units for which we are doing the performance analysis are called Decision Making Units (DMU). For example, we can compare all the McDonald’s outlets operating in the Delhi NCR Region to find out…

Continue Reading