Skip to main content


About Humalytica Analytics

The name, Humalytica, was intended to demonstrate a blend of Analytics and the Human Mind. As data science became a popular field, I began seeing people relying on software and black-box algorithms entirely too much. Analysts were picking their favorite tool or algorithm and forcing their data into it. For instance, an analyst might have learned and liked Artificial Neural Networks (ANN) and uses it to model every problem that comes their way, rather than picking the right algorithm and right tool for the job at hand.
HumalyticaTM Analytics attempt demonstrate that business problems can be solved with multiple methods/algorithms using multiple tools, and that there is an optimal solution among the larger solution set. We do this by blogging on multiple websites, and by providing training at conferences, workshops, and to companies directly.
Our tool expertise includes:
·       SAS Studio
·       SAS Enterprise Miner
·       SPSS Modeler
·       SPSS Stats
·       R Studio
·       Python
·       Python using Jupiter
·       MATLAB
·       Octave
·       SciLab
We also have expertise with the following algorithms:
·       Linear Regression
·       Logistic Regression
·       Generalized Linear Models
·       Random Forest
·       Empirical Bayes
·       Na├»ve Bayes
·       Artificial Neural Networks
·       Classification Trees
·       K-Means Clustering
·       And more…


Post a Comment

Popular posts from this blog

Time Series Analysis using iPython

Time Series Analysis using iPython In this example, we will examine ARMA and ARIMA models with Python using the Statsmodels package. This package can be downloaded at . Autogressive Moving-Average Processes (ARMA) and Auto-Regressive Integrated Moving Average (ARIMA) can be called from the tsa (Time Series) module from the Statamodels package. Note: I am not as expert in time-series analysis as I am in other areas of Analytics, so if you find errors I would be happy to know about them and correct them. Introduction ARIMA models are, in theory, the most general class of models for forecasting a time series, which can be made to be “stationary” by differencing (if necessary), perhaps in conjunction with nonlinear transformations such as logging or deflating (if necessary). A random variable that is a time series is stationary if its statistical properties are all constant over time. A stationary series has no trend

Neural Networks using R

Neural Networks using R By Jeffrey Strickland on May 13, 2015 The intent of this article is not to tell you everything you wanted to know about artificial neural networks (ANN) and were afraid to ask. For that you’ll have to ask someone else. Here I only intend to tell you how you might use R to implement an ANN model. One thing I will say is that I rarely use an ANN. I have found them to work best in an ensemble model (using averaging) with logistics regression models. Using neuralnet neuralnet depends on two other packages: grid and MASS ( Venables and Ripley, 2002). It is used is primarily with functions dealing with regression analyses like linear models ( lm ) and general linear models ( glm ). As essential arguments, we must specify a formula in terms of response variables ~ sum of covariates and a data set containing covariates and response variables. Default values are defined for all other parameters (see next subsection). We use the data set infert that i

Where Did All The Thinking Go?

Where Did All The Thinking Go?   “Thinking is the hardest work there is, which is probably the reason so few engage in it.” ― Henry Ford What Do We Really Want? We live in a fast-food society, at least in the USA. We want what we want, now! We prefer not to work too hard for it, if we work at all, and many of us have a sense of entitlement. We believe all of us should go to college and get our degree, but not much effort should be expended in doing so. After all, we have lots of cheeseburgers to munch on and many parties to attend. “Five percent of the people think; ten percent of the people think they think; and the other eighty-five percent would rather die than think.” ― Thomas A. Edison When I was teaching, even at the United States Military Academy, I ran into this attitude often. Students wanted to do the minimum amount of work to get by with a passing grade. In contrast were the non-traditional students taking evening classes after working a fulltime job dur