Blog Archives

Scraping twitter data to visualize trending tweets in Kuala Lumpur

September 30, 2018
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Scraping twitter data to visualize trending tweets in Kuala Lumpur

(Disclaimer: I’ve no grudge against python programming language per se. I think its equally great. In the following post, I’m merely recounting my experience.) It’s been quite a while since I last posted. The reasons are numerous, notable being,...

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To eat or not to eat! That’s the question? Measuring the association between categorical variables

May 31, 2017
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To eat or not to eat! That’s the question? Measuring the association between categorical variables

1. Introduction I serve as a reviewer to several ISI and Scopus indexed journals in Information Technology. Recently, I was reviewing an article, wherein the researchers had made a critical mistake in data analysis. They converted the original categor...

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Learning a classifier from census data

March 1, 2017
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Learning a classifier from census data

Introduction While reading the local daily, “The Star”, my attention was caught by headlines discussing an ongoing political or social discussion on the country’s financial state. Often, it is interesting to know the underlying cause of a certai...

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Predicting employment related factors in Malaysia- A regression analysis approach

February 20, 2017
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Predicting employment related factors in Malaysia- A regression analysis approach

Introduction A recent news article published in the national daily, The Star, reported, “The country’s unemployment rate has inched up by 0.1 percentage points to 3.5% in December 2016 compared to the previous month, according to the Statistics De...

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Predicting rubber plantation yield- A regression analysis approach

February 8, 2017
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Predicting rubber plantation yield- A regression analysis approach

Introduction Malaysia is the leading producer of natural rubber in the world. Being a leader in the production of natural rubber, Malaysia is contributing around 46% of total rubber production in the world. The rubber plantation was started in Malaysi...

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Basic assumptions to be taken care of when building a predictive model

January 17, 2017
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Basic assumptions to be taken care of when building a predictive model

Before starting to build on a predictive model in R, the following assumptions should be taken care off; Assumption 1: The parameters of the linear regression model must be numeric and linear in nature. If the parameters are non-numeric like categori...

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Data Transformations in R

January 10, 2017
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Data Transformations in R

A number of reasons can be attributed to when a predictive model crumples such as: Inadequate data pre-processing Inadequate model validation Unjustified extrapolation Over-fitting (Kuhn, 2013) Before we div...

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Sold! How do home features add up to its price tag?

September 6, 2016
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Sold! How do home features add up to its price tag?

I begin with a new project. It is from the Kaggle playground wherein the objective is to build a regression model (as the response variable or the outcome or dependent variable is continuous in nature) from a given set of predictors or independent var...

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Learning from data science competitions- baby steps

August 24, 2016
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Learning from data science competitions- baby steps

Off lately a considerable number of winner machine learning enthusiasts have used XGBoost as their predictive analytics solution. This algorithm has taken a preceedence over the traditional tree based algorithms like Random Forests and Neural Networks...

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Data Splitting

August 8, 2016
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Data Splitting

A few common steps in data model building are; Pre-processing the predictor data (predictor - independent variable's) Estimating the model parameters Selecting the predictors for the model Evaluating the model performance Fine tuning the class pr...

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