145 citations · 433 across the 14 of their papers we have counts for
7 papers · 1 filter
MentalChat16K: A Benchmark Dataset for Conversational Mental Health Assistance
Jia Xu, Tianyi Wei, Bojian Hou +7
We introduce MentalChat16K, an English benchmark dataset combining a synthetic mental health counseling dataset and a dataset of anonymized transcripts from interventions between B…
Clustering Alzheimer's Disease Subtypes via Similarity Learning and Graph Diffusion
Tianyi Wei, Shu Yang, Davoud Ataee Tarzanagh +6
Alzheimer's disease (AD) is a complex neurodegenerative disorder that affects millions of people worldwide. Due to the heterogeneous nature of AD, its diagnosis and treatment pose…
Benchmarking AutoML algorithms on a collection of synthetic classification problems
Pedro Henrique Ribeiro, Patryk Orzechowski, Joost Wagenaar +1
Automated machine learning (AutoML) algorithms have grown in popularity due to their high performance and flexibility to adapt to different problems and data sets. With the increas…
Generative and reproducible benchmarks for comprehensive evaluation of machine learning classifiers
Patryk Orzechowski, Jason H. Moore
Understanding the strengths and weaknesses of machine learning (ML) algorithms is crucial for determine their scope of application. Here, we introduce the DIverse and GENerative ML…
EBIC.JL -- an Efficient Implementation of Evolutionary Biclustering Algorithm in Julia
Paweł Renc, Patryk Orzechowski, Aleksander Byrski +2
Biclustering is a data mining technique which searches for local patterns in numeric tabular data with main application in bioinformatics. This technique has shown promise in multi…
EBIC: an evolutionary-based parallel biclustering algorithm for pattern discover
Patryk Orzechowski, Moshe Sipper, Xiuzhen Huang +1
In this paper a novel biclustering algorithm based on artificial intelligence (AI) is introduced. The method called EBIC aims to detect biologically meaningful, order-preserving pa…
PMLB: A Large Benchmark Suite for Machine Learning Evaluation and Comparison
Randal S. Olson, William La Cava, Patryk Orzechowski +2
The selection, development, or comparison of machine learning methods in data mining can be a difficult task based on the target problem and goals of a particular study. Numerous p…