36 citations · 103 across the 13 of their papers we have counts for
8 papers · 1 filter
Exploring LLM Capabilities in Extracting DCAT-Compatible Metadata for Data Cataloging
Lennart Busch, Daniel Tebernum, Gissel Velarde
Efficient data exploration is crucial as data becomes increasingly important for accelerating processes, improving forecasts and developing new business models. Data consumers ofte…
Cyber Security Data Science: Machine Learning Methods and their Performance on Imbalanced Datasets
Mateo Lopez-Ledezma, Gissel Velarde
Cybersecurity has become essential worldwide and at all levels, concerning individuals, institutions, and governments. A basic principle in cybersecurity is to be always alert. The…
An approach to melodic segmentation and classification based on filtering with the Haar-wavelet
Gissel Velarde, Tillman Weyde, David Meredith
We present a novel method of classification and segmentation of melodies in symbolic representation. The method is based on filtering pitch as a signal over time with the Haar-wave…
Wavelet-Filtering of Symbolic Music Representations for Folk Tune Segmentation and Classification
Gissel Velarde, Tillman Weyde, David Meredith
The aim of this study is to evaluate a machine-learning method in which symbolic representations of folk songs are segmented and classified into tune families with Haar-wavelet fil…
Performance of Machine Learning Classifiers for Anomaly Detection in Cyber Security Applications
Markus Haug, Gissel Velarde
This work empirically evaluates machine learning models on two imbalanced public datasets (KDDCUP99 and Credit Card Fraud 2013). The method includes data preparation, model trainin…
A Machine Learning Approach For Bitcoin Forecasting
Stefano Sossi-Rojas, Gissel Velarde, Damian Zieba
Bitcoin is one of the cryptocurrencies that is gaining more popularity in recent years. Previous studies have shown that closing price alone is not enough to forecast stock market…
An Open-Source and Reproducible Implementation of LSTM and GRU Networks for Time Series Forecasting
Gissel Velarde, Pedro Branez, Alejandro Bueno +2
This paper introduces an open-source and reproducible implementation of Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) Networks for time series forecasting. We evalua…
Tree Boosting Methods for Balanced andImbalanced Classification and their Robustness Over Time in Risk Assessment
Gissel Velarde, Michael Weichert, Anuj Deshmunkh +4
Most real-world classification problems deal with imbalanced datasets, posing a challenge for Artificial Intelligence (AI), i.e., machine learning algorithms, because the minority…