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Ramblings of a rogue Mathematician

System Identification using Gaussian Processes: Santa Fe Laser Data Set

System Identification For a short introduction to system identification and some common models refer to this previous post. Below I give a short tour of the Santa Fe Laser example which comes shipped with the DynaML machine learning library. Santa Fe Laser Generated Data The Santa Fe laser data is a standard benchmark data set in system identification. It serves as good starting point to start exploring time series models. It records only one observable...

System Identification using LSSVMs: Pont-sur-Sambre Power Plant

System Identification System identification refers to the process of learning a predictive model for a given dynamic system i.e. a system whose dynamics evolve with time. The most important aspect of these models is their structure, specifically the following are the common dynamic system models for discretely sampled time dependent systems. Nonlinear AutoRegresive (NAR) Signal modeled as a function of its previous values Nonlinear AutoRegressive with eXogenous inputs (NARX) Signal modeled as a function of...

Boston Housing Data: Gaussian Process Regression Models

Boston Housing Data The Housing data set is a popular regression benchmarking data set hosted on the UCI Machine Learning Repository. It contains 506 records consisting of multivariate data attributes for various real estate zones and their housing price indices. The task is then to learn a regression model that can predict the price index or range. In this blog post, I use the DynaML machine learning library to train the GP models. The following...