I came across an interesting blog that showcased Charting time series as calendar heat maps in R . It is based upon a great algorithm created by Paul Bleicher,CMO of Humedica. I'll let you link to the other blog to see more details on the background ...
As mentioned in prior posts, it is not possible to use the standard Weka GUI to instantiate a Genetic Algorithm, other than for feature selection. Part of the reason is that there is no generic algorithm to instantiate a fitness function. The same fl...
We started by discussing the goal of a genetic algorithm, which is to optimally find the candidate pool of rules that are superior to other potential rules. In our example of moving averages, we are seeking the values of parameters of the rule :if ma(...
I want to start with a brief introduction to what I consider one of the most powerful learning methodologies to come out of Artificial Intelligence in the last several decades-- the Genetic Algorithm. Although it was originally developed to model evol...
One of the buzzwords that seems to be common these days is AIS or Artificial Immune Systems. It is a biologically inspired classification type system that essentially tries to replicate some of our own natural immune system algorithms. Our bodies hav...
The prior introduction using a simple model to determine next weeks change based on the S&P 500 index and VIX did not look very promising, although hopefully it served to familiarize yourself with how classification is used in augmenting trading decisi...
The neural network tutorial focused on a type of method known as regression. The other common method utilized in machine learning is called classification. The two approaches are somewhat similar in that they identify the best possible curve to learn...
Following is an example of what it looks like to predict an actual univariate price series. The period of the signal that was sampled was already in stationary form, so not much massaging was needed other than normalization (described earlier).What's ...
Consider this an introduction to how we need to pre-process the data.I mentioned earlier that a financial time series is typically a unit root or non-stationary signal, what this means is that if you sample statistical properties over time, they will o...
Ok, now that we have seen how well the perfect sine wave signal was learned, let's turn it up a notch and see how well the complex sine wave was learned.Fig 1. Summary of Actual Vs. Predicted out of sample complex sine waveformUh Oh. What happened, the...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
