Results 41 to 50 of about 6,391,262 (321)
Smooth Symbolic Regression: Transformation of Symbolic Regression into a Real-Valued Optimization Problem [PDF]
The typical methods for symbolic regression produce rather abrupt changes in solution candidates. In this work, we have tried to transform symbolic regression from an optimization problem, with a landscape that is so rugged that typical analysis methods do not produce meaningful results, to one that can be compared to typical and very smooth real ...
Erik Pitzer, Gabriel Kronberger
openaire +3 more sources
Globally Optimal Symbolic Regression [PDF]
International audienceIn this study we introduce a new technique for symbolic regression that guarantees global optimality. This is achieved by formulating a mixed integer non-linear program (MINLP) whose solution is a symbolic mathematical expression of
Dash, Sanjeeb +6 more
core +3 more sources
Online Symbolic Regression with Informative Query
Symbolic regression, the task of extracting mathematical expressions from the observed data, plays a crucial role in scientific discovery. Despite the promising performance of existing methods, most of them conduct symbolic regression in an offline ...
Jin, Pengwei +7 more
core +2 more sources
Symbolic regression for the interpretation of quantitative structure-property relationships
The interpretation of quantitative structure–activity or structure–property relationships is important in the field of chemoinformatics. Although multivariate linear regression models are typically interpretable, they do not generally have high ...
Katsushi Takaki, Tomoyuki Miyao
doaj +1 more source
This work explores an interpretable approach based on physics-informed neural networks (PINNs) combined with symbolic regression (SR) to determine mathematical expressions for the predicted solutions of nonlinear partial differential equations that ...
Joyabrata Das +3 more
semanticscholar +1 more source
The Lookup Table Regression Model for Histogram-Valued Symbolic Data
This paper presents the Lookup Table Regression Model (LTRM) for histogram-valued symbolic data. We first transform the given symbolic data to a numerical data table by the quantile method.
Manabu Ichino
doaj +1 more source
Exhaustive Symbolic Regression
15 pages, 7 figures, 2 tables.
Deaglan J. Bartlett +2 more
openaire +6 more sources
Hybrid Symbolic Regression with the Bison Seeker Algorithm
This paper focuses on the use of the Bison Seeker Algorithm (BSA) in a hybrid genetic programming approach for the supervised machine learning method called symbolic regression.
Jan Merta
doaj +1 more source
The efficiency of active learning (AL) approaches to identify materials with desired properties relies on the knowledge of a few parameters describing the property.
Akhil S. Nair +2 more
semanticscholar +1 more source
Symbolic Regression Algorithms with Built-in Linear Regression
Recently, several algorithms for symbolic regression (SR) emerged which employ a form of multiple linear regression (LR) to produce generalized linear models. The use of LR allows the algorithms to create models with relatively small error right from the beginning of the search; such algorithms are thus claimed to be (sometimes by orders of magnitude ...
Jan Zegklitz, Petr Posík
openaire +2 more sources

