women’s style recommendation with artificial intelligence (part #2)

In “women’s style recommendation with artificial intelligence (part #1)”, I introduced my work toward developing artificial intelligence (AI) for fashion and style recommendation. Essentially, its an expert system built on a Bayesian belief network. Now I discuss model validation and next steps in the design iteration process. I first wanted to see if the trained […]

women’s style recommendation with artificial intelligence (part #1)

Introduction We know several basic style “rules” (ha!) based on body shape: Skirts: “Apple” Body Shape: IF body shape is apple AND skirt has front zipper THEN don’t wear IF body shape is apple AND skirt has side zipper THEN wear IF body shape is apple AND skirt has no zipper THEN wear “Rectangular” Body […]

toward a gene panel for psychiatric violence

I recently developed a method for specifying a comprehensive gene list for investigating genes related to psychiatric violence, which I describe below. First though, here’s a cool picture from the analysis: Method I started by extracting a list of diseases involving violence from [1], removing epilepsy, dementia, mental retardation (is there a better word for […]

machine learning in FOREX (part one: establishing a performance baseline)

Introduction We’ve been applying machine learning to FOREX price prediction. The performance of our models varies widely, so to establish a baseline we created a simple linear regression model with which we can compare performance of more sophisticated models against. What We Are Trying To Do Given a time-series of 26 four-hour price samples, we […]

autocorrelation in FOREX

To inform the construction of a machine learning-based price prediction algorithm, we want to understand how many lags prove statistically significant with regard to autocorrelation in the seven major FOREX pairs. So we first choose 10,000 random time points between January 1, 2000 and January 1, 2017 for each of the seven pairs. Then we […]

demonstrating a simple expert system with cascading effects (Clojure version)

We originally implemented this demonstration in CLIPS (see this post) but decided Clojure would provide a better platform due to advantages discussed below. “An expert system is a program capable of pairing up a set of facts with a set of rules to those facts, and execute some actions based on the matching rules. [1]” […]

encoding fashion rules into mathematical data structures (part one)

As we build our fashion recommendation engine, we seek rules to populate it with. With few exceptions (e.g. [1]), we find these rules encoded in prose or infographic form, rather than a semantic web form suitable for computation. For example, [2] provides written advice on dressing fabulously for a “rectangular” women’s body type. The writers […]

demonstrating a simple expert system with cascading effects (CLIPS version)

We demonstrate a more modern implementation of this system in Clojure here. “An expert system is a program capable of pairing up a set of facts with a set of rules to those facts, and execute some actions based on the matching rules. [1]” At 180 centimeters, Emily Williams stands tall. She carries a “rectangular” […]

summary of our FOREX experiments and next steps

We started by building a support vector machine model based on features used in harmonic trading, with the idea that ideal “harmonic” ratios can be learned rather than explicitly specified. This worked on testing sets but not when we started trading with it. We abandoned the model before we realized that we need to manage […]