Tag: Et Cetra

SAS -Silverlight Champion – Alan Churchill

st1\:*{behavior:url(#ieooui) }

/* Style Definitions */
table.MsoNormalTable
{mso-style-name:”Table Normal”;
mso-tstyle-rowband-size:0;
mso-tstyle-colband-size:0;
mso-style-noshow:yes;
mso-style-parent:””;
mso-padding-alt:0in 5.4pt 0in 5.4pt;
mso-para-margin:0in;
mso-para-margin-bottom:.0001pt;
mso-pagination:widow-orphan;
font-size:10.0pt;
font-family:”Times New Roman”;}

Alan Churchill

Leading SAS and .Net Expert ,

MS Silverlight Evangelist

Analytics Entrepreneur and Mentor to SAS Consultants

1) What’s the latest trend you see in Computer Programming over the next
year and next three to five years.

Silverlight and Flex will be huge and will really enable much more SaaS. The current web simply needs wholesale replacement to make it more usable for business applications. These new RIAs will allow us, as developers, to take it to a whole new level. Expect a massive influx of dollars into web redesign and redevelopment.

2) Tell us how you came in this field of work, and what factors made
you succeed.

I got into computers in high school (this was very early computing). I loved the sense of challenge that computers offered: they were a big crossword puzzle. I succeeded because I never viewed a problem the way a typical computer person or scientist would view them. As a history guy, I took a more holistic approach to problems. Heck, if you don’t know about a particular theory, you won’t be constrained by it. If you do know it, sometimes ignore it to get the job done, even if it isn’t as pretty. Continue reading “SAS -Silverlight Champion – Alan Churchill”

Analytics through the Browser : Strata

image

Here is an interesting concept of a data browser called Strata by a company called Kirix ( http://www.kirix.com/ ). It promises to connect your online , offfline data and help you perform analytics on it. It has a 30 days trial version . I am currently evaluating and will keep you posted.

This is one more example of analytics moving online ,from packaged software .

The Ohri Framework – Data Mining on Demand

The Ohri Framework tries to create an economic alternative to proprietary data mining softwares by giving more value to the customer and utilizing open source statistical package R , with the GUI Rattle , hosted on a cloud computing environment.

It is based on the following assumptions-

1) R is relatively inefficient in processing bigger file sizes on same desktop configuration as other softwares like SAS.

2) R has a steep learning curve , hence the need for the GUI Rattle .

3) The enhanced need for computing resources for R is best solved using a cloud computing on demand processing environment. This enables R to scale up to whatever processing power it needs. Mainstream data mining softwares charge by CPU count for servers and are much more expensive due to software costs alone.

Continue reading “The Ohri Framework – Data Mining on Demand”

The Empire Strikes Back- MS Products in the wings

MS Products in the wings can be accessed on connect.microsoft.com/

They are extensive, and Steve (Ballmer not Jobs) is using most of the 44 Billion he saved (thanks to Jerry ‘s merry ways) to create savvy tools to match Google in anything they make and more.

Yes the tools are that good.And No, they are only limited to the US as of now.

ROC Curve

ROC Curve is a nice modeling concept to know as it will used practically in nearly all models

irrespective of spoefic technique and irrespective of statistical software.

We use the Wikipedia for referring to easy to implement statistics rather than crusty

thick books which seem prohibitely dense and opaque to outsiders

-This is how you define the ROC Curve.

actual value
p n total
prediction
outcome		 p’ True
Positive		 False
Positive		 P’
n’ False
Negative		 True
Negative		 N’
total P N

true positive (TP)

eqv. with hit
true negative (TN)
eqv. with correct rejection
false positive (FP)
eqv. with false alarm, Type I error
false negative (FN)
eqv. with miss, Type II error
true positive rate (TPR)
eqv. with hit rate, recall, sensitivity
TPR = TP / P = TP / (TP + FN)
false positive rate (FPR)
eqv. with false alarm rate, fall-out
FPR = FP / N = FP / (FP + TN)
accuracy (ACC)
ACC = (TP + TN) / (P + N)
specificity (SPC)
SPC = TN / (FP + TN) = 1 ? FPR
positive predictive value (PPV)
eqv. with precision
PPV = TP / (TP + FP)

Here is a good java enabled page to calculate the ROC Curve.

http://www.rad.jhmi.edu/jeng/javarad/roc/JROCFITi.html

And in case any one asks, ROC stands for Receiver Operating Characteristic. ……