Simple Machine Learning Models on OrderBook/PositionBook Features
This post is about using OrderBook/PositionBook features as input to simple machine learning models after previous investigation into the relevance of such […]
Read moreCategory: Feature extraction
OrderBook and PositionBook Features
In my previous post I talked about how I planned to use constrained optimization to create features from Oanda’s OrderBook and PositionBook data, which […]
Read moreMore Work on RVFL Networks
Back in November last year I posted about Random Vector Functional Link (RVFL) networks here and here. Since then, along with my […]
Read moreIdeal Cyclic Tau Embedding as Times Series Features
Continuing on from my Ideal Tau for Time Series Embedding post, I have now written an Octave function based on these ideas […]
Read moreUsing the BayesOpt Library to Optimise my Planned Neural Net
Following on from my last post, I have recently been using the BayesOpt library to optimise my planned neural net, and this post […]
Read moreRefactored Denoising Autoencoder Update #2
Below is this second code update. % select rolling window length to use – an optimisable parameter via pso? rolling_window_length = 50 […]
Read moreGiving up on Runge-Kutta Methods (for now?)
Over the last few weeks I have been looking at using Runge-Kutta methods for the creation of features, but I have decided […]
Read moreRunge-Kutta Example and Code
Following on from my last post I thought I would, as a first step, code up a “straightforward” Runge-Kutta function and show how […]
Read moreRunge-Kutta Methods
As stated in my previous post I have been focusing on getting some meaningful features as possible inputs to my machine learning […]
Read moreRecent reading
In my last post I mentioned that I was going away for the summer, but now I’m back. During the summer I […]
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