Introduction In my last article, I presented Python programming using iPython. There, I used an example of logistic regression modeling for mothers with children having low birth weights. In this article, using […]
Random Forest using iPython
Jeffrey Strickland
Jeffrey Strickland, Ph.D., is the Author of “Predictive Analytics Using R” and a Senior Analytics Scientist with Clarity Solution Group. He has performed predictive modeling, simulation and analysis for the Department of Defense, NASA, the Missile Defense Agency, and the Financial and Insurance Industries for over 20 years. Jeff is a Certified Modeling and Simulation professional (CMSP) and an Associate Systems Engineering Professional. He has published nearly 200 blogs on LinkedIn, is also a frequently invited guest speaker and the author of 20 books including:
•Operations Research using Open-Source Tools
•Discrete Event simulation using ExtendSim
•Crime Analysis and Mapping
•Missile Flight Simulation
•Mathematical Modeling of Warfare and Combat Phenomenon
•Predictive Modeling and Analytics
•Using Math to Defeat the Enemy
•Verification and Validation for Modeling and Simulation
•Simulation Conceptual Modeling
•System Engineering Process and Practices
•Weird Scientist: the Creators of Quantum Physics
•Albert Einstein: No one expected me to lay a golden eggs
•The Men of Manhattan: the Creators of the Nuclear Era
•Fundamentals of Combat Modeling
•LinkedIn Memoirs
•Quantum Phaith
•Dear Mister President
•Handbook of Handguns
•Knights of the Cross: The True Story of the Knights Templar
Logistic Regression with iPython
Introduction IPython is a growing project, with increasingly language-agnostic components. IPython 3.x was the last monumental release of IPython, containing the notebook server, qtconsole, etc. As of IPython 4.0, the language-agnostic parts […]
What R KNIME?
There is absolutely nothing wrong with my grammar, at least in the title. If you do not know what R is, you should probably visit the boutique section on Amazon instead of […]
Analytics: is it more than a buzzword?
Who performs analytics? Before we approach a formal definition, it may be useful to consider who performs analytics. Traditionally, analytics has been performed by statisticians, operations research analysts and management scientist. More […]
Give it a Lift: Uplift Modeling
Uplift modeling, also known as incremental modeling, true lift modeling, or net-lift modeling is a predictive modeling technique that directly models the incremental impact of a treatment (such as a direct marketing […]
You R not going to believe this
Next time I build a predictive model in R and I am just not getting anywhere with it, I think I will try Minesweeper? Most of you probably know this, but the […]
The Skills and Tools of Predictive Analytics
I am always at a loss in describing the skills of predictive analytics, for there are many. I am working on another book about analytics that has a different approach than Predictive Analytics using R, though I am using material from three chapters. The new book is an operations research approach to analytics, covering a different set of methods, skill and tools. Combined, the two books are over 1000 pages, so perhaps you can see my dilemma. Hence, this article is going to touch the basic skills required and several useful tool.
Humalytica Strikes Again
The Analytics Post, Wednesday, August 6, 2015 The most unpopular, fastest decaying piece of analytics software today, Humalytica, a.k.a. the human mind, is reportedly trying to engage model builders to use rational […]
What is Humalytica?
The Question Recently, a group of analysts were asked this question: “In your opinion, if you had to pick only one, what is the best analytics tool in the marketplace?” My answer […]
What the heck are Association Rules in Analytics?
It could be said that if you go to the grocery store and buy some Captain Crunch (once my favorite cereal) you would also be more likely to buy milk. Association Rules […]
BI Corner 