Associate professor University of Alcala
danrodgar Goto Github PK
Name: Daniel Rodriguez
Type: User
Company: University of Alcala
Bio: Associate Professor University of Alcala
Location: Madrid, Spain
Daniel Rodriguez's Projects
aicourse
Slides about different topics related to Artificial Intelligence.
aix360
Interpretability and explainability of data and machine learning models
app-moviecards
atoml
Automated testing of machine learing
baycomp
Bayesian Comparison
bidas4pca
Source code for the PCA generated for BiDAS4
boruta_py
Python implementations of the Boruta all-relevant feature selection method.
complexitysoftwaredefectsdatasets
computingproject
Despite having no time whatsoever, I have to do an entire project to finish my degree. Here it is.
contextlearning
danrodgar
Personal site
dase
Data Analysis in Software Engineering
datacourse
Data Science lectures.
dataminingse
Data Mining in Software Engineering (and Vice versa)
dcol
The data complexity library, DCoL, is a machine learning software that implements all metrics to characterize the apparent complexity of classification problems. The code is implemented in C++ and can be run on multiple platforms.
defectpredictionsofteng
defpreddatasets
dissertation-toby-bligh
dissertation_19043695
ecml2016
Matlab code of the paper "Measuring the Stability of Feature Selection" by Sarah Nogueira and Gavin Brown (University of Manchester) submitted to ECML 2016.
ecol
Extended Complexity Library in R
elap2022
Sitio web de la Escuela Latinoamericana de Aprendizaje Profundo 2022.
etc3550slides
Slides for a forecasting course based on fpp2
gitslides
ifuah
LaTeX templates for teaching and research documents from the Polytechnic School, University of Alcalá (UAH), based on the template made by Borja Calvo for the Computer Science Faculty (UPV/EHU)
imbalancedegree
Measures for the class-imbalance extent of a given dataset
introdm
Slides Introduction to Data Mining
introunittesting
Introduction to Unit Testing
issta21-jit-dp
This repo illustrates how to evaluate the artifacts in the paper Deep Just-in-Time Defect Prediction: How Far Are We? published in ISSTA'21.
jmlr2018
The code of the experiments of the submitted paper "On the stability of Feature Selection" in Matlab, R and Python.
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