Introduction: Random Forest Now that we have an idea about decision trees and how exactly they work, I think we can now go a step further and try to improve our decision tree models by introducing a very basic but very effective extension for decision trees, which are popularly known as “Random Forest”. To understand decision trees in detail, you…

## All you want to know about Decision Tree Part 3

Decision Tree Part 3 This is the third article in the decision tree series, you can access other two here: Part 1: All you need to know about Decision Tree Part 1) Part 2: All you need to know about Decision Tree Part 2) In this previous article, I tried to construct a decision tree using R. For this, I have considered…

## All you need to know about Decision Tree-Part 2

Introduction In my previous article, (All you need to know about Decision Tree Part 1), we have discussed on how a decision tree looks like, its terminology and we also have seen an example of a decision tree. Now that you got a basic idea on decision tree, in this article, I will discuss on some of the major concepts…

## Text Analytics: Mining Enron Emails

Mining Enron Emails You might have heard about the Enron scandal that came to light in 2001 which eventually led to bankruptcy of the Enron corporation. This is the largest corporate fraud that had happened so far. The Enron top-honchos used what is called Mark-to-market accounting to make up their financial statements. They used this accounting and financial shenanigan to…

## Activation Functions in ANNs (Conclusion)

In my last article Activation Functions in ANNs, we discussed on few activation functions, now let’s explore more on some other available activation functions. Tanh Function These are scaled sigmoid function which is similar to sigmoid functions. Or It is nonlinear so we can have more than one layer of neurons depending upon the requirement. Its range is (-1, 1).…

## All you need to know about Decision Tree (Part-1)

Introduction As the title suggests, I’ll try to put necessary information on decision tree under this article. However, providing all the required information in one post will be difficult and makes you lost. So, I’ve made this article into three parts. Part 1 (this post) : we shall discuss introduction and definitions Part 2 : Advanced topics related to decision…

## 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…

## Activation Functions in ANNs (Part-1)

Introduction In an ANN the activation function of a node is defined as the threshold after which the node will produce an output given an input or set of inputs. Activation functions can be linear or non-linear but mostly nonlinear functions are being used in ANNs. This is a very important in the way a network learns because in light…