31 citations · 38 across the 9 of their papers we have counts for
9 papers
Autorelevance function and other feature relevance measures for univariate time series
Julian Cardenas, Jamie Arjona, Pedro Delicado
We propose a model agnostic methodology to measure lag relevance in machine learning forecasting models applied to univariate time series. Particularly, we are working in the conte…
Modeling continuous monitoring glucose curves by Beta generalized non-parametric models
Nihan Acar-Denizli, Pedro Delicado
We present a functional data analysis approach for studying time-dependent, continuous glucose monitoring data with repeated measures for each individual in an experiment. After sc…
Functional relevance based on the continuous Shapley value
Pedro Delicado, Cristian Pachón-García
The presence of artificial intelligence (AI) in our society is increasing, which brings with it the need to understand the behavior of AI mechanisms, including machine learning pre…
Functional Data Analysis on Wearable Sensor Data: A Systematic Review
Nihan Acar-Denizli, Pedro Delicado
Wearable devices and sensors have recently become a popular way to collect data, especially in the health sciences. The use of sensors allows patients to be monitored over a period…
SurvLIMEpy: A Python package implementing SurvLIME
Cristian Pachón-García, Carlos Hernández-Pérez, Pedro Delicado +1
In this paper we present SurvLIMEpy, an open-source Python package that implements the SurvLIME algorithm. This method allows to compute local feature importance for machine learni…
Wildfires vegetation recovery through satellite remote sensing and Functional Data Analysis
Feliu Serra-Burriel, Pedro Delicado, Fernando M. Cucchietti
In recent years wildfires have caused havoc across the world, especially aggravated in certain regions, due to climate change. Remote sensing has become a powerful tool for monitor…
Estimating heterogeneous wildfire effects using synthetic controls and satellite remote sensing
Feliu Serra-Burriel, Pedro Delicado, Andrew T. Prata +1
Wildfires have become one of the biggest natural hazards for environments worldwide. The effects of wildfires are heterogeneous, meaning that the magnitude of their effects depends…
Multidimensional Scaling for Big Data
Pedro Delicado, Cristian Pachón-García
We present a set of algorithms implementing multidimensional scaling (MDS) for large data sets. MDS is a family of dimensionality reduction techniques using a distance…
Understanding complex predictive models with Ghost Variables
Pedro Delicado, Daniel Peña
We propose a procedure for assigning a relevance measure to each explanatory variable in a complex predictive model. We assume that we have a training set to fit the model and a te…