53 citations · 106 across the 8 of their papers we have counts for
6 papers · 1 filter
Explanation Method for Anomaly Detection on Mixed Numerical and Categorical Spaces
Iñigo López-Riobóo Botana, Carlos Eiras-Franco, Julio Hernandez-Castro +1
Most proposals in the anomaly detection field focus exclusively on the detection stage, specially in the recent deep learning approaches. While providing highly accurate prediction…
Explain and Conquer: Personalised Text-based Reviews to Achieve Transparency
Iñigo López-Riobóo Botana, Verónica Bolón-Canedo, Bertha Guijarro-Berdiñas +1
There are many contexts in which dyadic data are present. Social networks are a well-known example. In these contexts, pairs of elements are linked building a network that reflects…
E2E-FS: An End-to-End Feature Selection Method for Neural Networks
Brais Cancela, Verónica Bolón-Canedo, Amparo Alonso-Betanzos
Classic embedded feature selection algorithms are often divided in two large groups: tree-based algorithms and lasso variants. Both approaches are focused in different aspects: whi…
On the effectiveness of convolutional autoencoders on image-based personalized recommender systems
E. Blanco-Mallo, B. Remeseiro, V. Bolón-Canedo +1
Recommender systems (RS) are increasingly present in our daily lives, especially since the advent of Big Data, which allows for storing all kinds of information about users' prefer…
A scalable saliency-based Feature selection method with instance level information
Brais Cancela, Verónica Bolón-Canedo, Amparo Alonso-Betanzos +1
Classic feature selection techniques remove those features that are either irrelevant or redundant, achieving a subset of relevant features that help to provide a better knowledge…
Distributed Correlation-Based Feature Selection in Spark
Raul-Jose Palma-Mendoza, Luis de-Marcos, Daniel Rodriguez +1
CFS (Correlation-Based Feature Selection) is an FS algorithm that has been successfully applied to classification problems in many domains. We describe Distributed CFS (DiCFS) as a…