Due to their flexibility and superior performance, machine learning mode...
The expected goal models have gained popularity, but their interpretabil...
The machine learning modeling process conventionally culminates in selec...
Lung cancer and covid-19 have one of the highest morbidity and mortality...
Explainable AI (XAI) is an increasingly important area of research in ma...
Imbalanced data poses a significant challenge in classification as model...
Machine learning applications cover a wide range of predictive tasks in ...
Explainable artificial intelligence (XAI) methods are portrayed as a rem...
Prevention is better than cure. This old truth applies not only to the
p...
As deep learning models increasingly find applications in critical domai...
To what extent can the patient's length of stay in a hospital be predict...
The prediction of age is a challenging task with various practical
appli...
Predictive modelling is often reduced to finding the best model that
opt...
This paper introduces HADES, a novel tool for automatic comparative docu...
The number of standardized policy documents regarding climate policy and...
Machine and deep learning survival models demonstrate similar or even
im...
The data revolution has generated a huge demand for data-driven solution...
The expected goal provides a more representative measure of the team and...
For many machine learning models, a choice of hyperparameters is a cruci...
The increased interest in deep learning applications, and their
hard-to-...
The growing number of AI applications, also for high-stake decisions,
in...
The increasing number of regulations and expectations of predictive mach...
Many methods have been developed to understand complex predictive models...
The relevance of the Key Information Extraction (KIE) task is increasing...
Rapid development of advanced modelling techniques gives an opportunity ...
One of the key elements of explanatory analysis of a predictive model is...
Machine learning decision systems are getting omnipresent in our lives. ...
The increasing amount of available data, computing power, and the consta...
The sudden outbreak and uncontrolled spread of COVID-19 disease is one o...
A major requirement for credit scoring models is to provide a maximally
...
The growing availability of data and computing power fuels the developme...
Finding optimal hyperparameters for the machine learning algorithm can o...
Incomplete data are common in practical applications. Most predictive ma...
Measures for evaluation of model performance play an important role in
M...
When analysing a complex system, very often an answer for one question r...
State-of-the-art solutions for Natural Language Processing (NLP) are abl...
Meta learning is a difficult problem as the expected performance of a mo...
Complex black-box predictive models may have high performance, but lack ...
Recently we see a rising number of methods in the field of eXplainable
A...
Recent developments in Named Entity Recognition (NER) have resulted in b...
The most important part of model selection and hyperparameter tuning is ...
Predictive modeling has an increasing number of applications in various
...
Is it true that patients with similar conditions get similar diagnoses? ...
Explainable Artificial Intelligence (XAI) brings a lot of attention rece...
The increasing availability of large but noisy data sets with a large nu...
Complex black-box predictive models may have high accuracy, but opacity
...
Deep Learning NLP domain lacks procedures for the analysis of model
robu...
Machine learning models have spread to almost every area of life. They a...
Machine learning has spread to almost every area of life. It is successf...
In this paper we present the results of an investigation of the importan...