Open Source Analytics » Modeling

Data Mining – Desktop Survival Guide

Nishith — Fri, 10 Mar 2006 08:19:38 +0000

A good resource on Data Mining using R environment is “Data Mining – Desktop Survival Guide” by Graham Williams. Its a well researched and frequently updated free online book. Graham does a good job of going through the data mining process and provides detailed descriptions of the commonly used algorithms.

Exmaples are in R (all with R source code, of course), with some good examples of graphical visualization as well.

Click here for Data Mining – Desktop Survival Guide

R Environment is a part of DecisionStudio-Professional and can also be separately downloaded from http://r-project.org.

Econometrics on R Environment

Nishith — Mon, 06 Mar 2006 20:56:15 +0000

I would, in due course, spend some time on the R Environment (available as part of DecisionStudio Professional, and separately downloadable from http://r-project.org). R provides an excellent alternative to commercial products for modeling, statistical analysis, and graphics. Originally designed by AT&T Bell Labs, the R environment is fast becoming the standard for cutting edge number crunching.

Bio-informatics is one area of dominance, and a lot of academic papers these days come with R based/compatible implementations. (So you don’t have to wait for your commercial BI vendor to first discover that new technique, make up its mind about it, and then finally get a bunch of disinterested code-monkeys to write a new library for, luckily just in time for the release after next).

While R is used a lot for statistical research, its adoption for econometrics has been comparatively slower, possibly due to terminology differences.

An excellent text called “Econometrics in R” by Grant V. Farnsworth (PDF) provides a effective hands-on intro to the most common things you would find yourself doing including Time Series, regressions, Plotting, etc. Have a look.

DecisionStudio Professional – Desktop BI Platform

Nishith — Tue, 28 Feb 2006 17:39:34 +0000

On Friday we released DecisionStudio Professional – a comprehensive and free desktop BI Platform that gives you all the tools needed for analytics under a single package licensed under GNU Public License (GPL).

DecisionStudio Professional (DSP) is an advanced graphical data mining, reporting, modeling, and analysis environment built on top of the best-of-breed open source projects. Some of these include:
— Optimized MySQL database as data warehouse platform
— SQL Workbench (MySQL Query Browser and DBDesigner) for Data Analysts
— R environment for statistical analysis and modeling
— iReport Reporting GUI and JasperReport reporting library
— Python with Boa Constructor IDE for application and GUI development

DecisionStudio Professional is the only end-to-end open source analytics platform that provides comprehensive capabilities to each role. Data Analysts get to store, process, and publish data on a standard MySQL platform; Reporting Analysts would like iReport and the integration with Office tools; and Modelers would love the excellent R Environment. It also includes Python along with a drag-n-drop GUI building environment for analytics Application Developers.

You can find out more about DecisionStudio Professional at decisionstudio.com, and can download your copy at Sourceforge.net. Click here to download the product brochure (PDF).

Go ahead, it’s completely free and will always stay so.

Classification Trees (Decision Trees)

Nishith — Tue, 06 Dec 2005 16:53:58 +0000

Decision trees are one of the most widely used and practical forms of machine learning and data mining. They have been widely researched and applied to a large variety of data mining problems. (Decision trees are also known as Classification Trees or Regression Trees based on whether the classification is being done on real values or on categorical variables.)

Trees are used to predict the membership of new cases into existing classes based on some information. As an example, the classification of a new loan applicant into risk-based categories can give a bank an idea of how the applicant is likely to perform on his/her loan. The bank can use this information to approve/reject the loan, and/or to price the loan based on risk. (Riskier applicants get more expensive loans).

A simple Decision Tree to predict attendance at a Golf CLub based on the weather can be found at Wikipedia::Decision Trees

Decision tree models are built by a process that is known as recursive partitioning. Click here for a more detailed explanation of the process.