74 citations · 135 across the 9 of their papers we have counts for
9 papers
Interpretable Symbolic Regression for Data Science: Analysis of the 2022 Competition
F. O. de Franca, M. Virgolin, M. Kommenda +21
Symbolic regression searches for analytic expressions that accurately describe studied phenomena. The main attraction of this approach is that it returns an interpretable model tha…
Prediction Intervals and Confidence Regions for Symbolic Regression Models based on Likelihood Profiles
Fabricio Olivetti de Franca, Gabriel Kronberger
Symbolic regression is a nonlinear regression method which is commonly performed by an evolutionary computation method such as genetic programming. Quantification of uncertainty of…
Transformation-Interaction-Rational Representation for Symbolic Regression
Fabricio Olivetti de Franca
Symbolic Regression searches for a function form that approximates a dataset often using Genetic Programming. Since there is usually no restriction to what form the function can ha…
Using Shape Constraints for Improving Symbolic Regression Models
Christian Haider, Fabricio Olivetti de França, Bogdan Burlacu +1
We describe and analyze algorithms for shape-constrained symbolic regression, which allows the inclusion of prior knowledge about the shape of the regression function. This is rele…
Shape-constrained Symbolic Regression -- Improving Extrapolation with Prior Knowledge
Gabriel Kronberger, Fabricio Olivetti de França, Bogdan Burlacu +2
We investigate the addition of constraints on the function image and its derivatives for the incorporation of prior knowledge in symbolic regression. The approach is called shape-c…
Enhanced word embeddings using multi-semantic representation through lexical chains
Terry Ruas, Charles Henrique Porto Ferreira, William Grosky +2
The relationship between words in a sentence often tells us more about the underlying semantic content of a document than its actual words, individually. In this work, we propose t…
EvoMan: Game-playing Competition
Fabricio Olivetti de Franca, Denis Fantinato, Karine Miras +2
This paper describes a competition proposal for evolving Intelligent Agents for the game-playing framework called EvoMan. The framework is based on the boss fights of the game call…
DCDistance: A Supervised Text Document Feature extraction based on class labels
Charles Henrique Porto Ferreira, Debora Maria Rossi de Medeiros, Fabricio Olivetti de França
Text Mining is a field that aims at extracting information from textual data. One of the challenges of such field of study comes from the pre-processing stage in which a vector (an…
Enhanced perceptrons using contrastive biclusters
André L. V. Coelho, Fabrício O. de França
Perceptrons are neuronal devices capable of fully discriminating linearly separable classes. Although straightforward to implement and train, their applicability is usually hindere…