40 citations · 46 across the 4 of their papers we have counts for
4 papers
Interpreting Models via Single Tree Approximation
Yichen Zhou, Giles Hooker
We propose a procedure to build a decision tree which approximates the performance of complex machine learning models. This single approximation tree can be used to interpret and s…
Functional Principal Components Analysis of Spatially Correlated Data
Chong Liu, Surajit Ray, Giles Hooker
This paper focuses on the analysis of spatially correlated functional data. The between-curve correlation is modeled by correlating functional principal component scores of the fun…
Maximal Autocorrelation Functions in Functional Data Analysis
Giles Hooker, Steven Roberts
This paper proposes a new factor rotation for the context of functional principal components analysis. This rotation seeks to re-represent a functional subspace in terms of directi…
Truncated Linear Models for Functional Data
Peter Hall, Giles Hooker
A conventional linear model for functional data involves expressing a response variable in terms of the explanatory function , via the model: $Y=a+\int_I b(t)X(t)dt+\hbox…