4 citations · 12 across the 17 of their papers we have counts for
4 papers · 1 filter
OSTSC: Over Sampling for Time Series Classification in R
Matthew Dixon, Diego Klabjan, Lan Wei
The OSTSC package is a powerful oversampling approach for classifying univariant, but multinomial time series data in R. This article provides a brief overview of the oversampling…
A High Frequency Trade Execution Model for Supervised Learning
Matthew F Dixon
This paper introduces a high frequency trade execution model to evaluate the economic impact of supervised machine learners. Extending the concept of a confusion matrix, we present…
Sequence Classification of the Limit Order Book using Recurrent Neural Networks
Matthew F Dixon
Recurrent neural networks (RNNs) are types of artificial neural networks (ANNs) that are well suited to forecasting and sequence classification. They have been applied extensively…
Deep Learning for Spatio-Temporal Modeling: Dynamic Traffic Flows and High Frequency Trading
Matthew F. Dixon, Nicholas G. Polson, Vadim O. Sokolov
Deep learning applies hierarchical layers of hidden variables to construct nonlinear high dimensional predictors. Our goal is to develop and train deep learning architectures for s…