Code2vect: An efficient heterogenous data classifier and nonlinear regression technique
Article dans une revue avec comité de lecture
The aim of this paper is to present a new classification and regression algorithm based on Artificial Intelligence. The main feature of this algorithm, which will be called Code2Vect, is the nature of the data to treat: qualitative or quantitative and continuous or discrete. Contrary to other artificial intelligence techniques based on the “Big-Data,” this new approach will enable working with a reduced amount of data, within the so-called “Smart Data” paradigm. Moreover, the main purpose of this algorithm is to enable the representation of high-dimensional data and more specifically grouping and visualizing this data according to a given target. For that purpose, the data will be projected into a vectorial space equipped with an appropriate metric, able to group data according to their affinity (with respect to a given output of interest). Furthermore, another application of this algorithm lies on its prediction capability. As it occurs with most common data-mining techniques such as regression trees, by giving an input the output will be inferred, in this case considering the nature of the data formerly described. In order to illustrate its potentialities, two different applications will be addressed, one concerning the representation of high-dimensional and categorical data and another featuring the prediction capabilities of the algorithm.
Showing items related by title, author, creator and subject.
On the Proper Generalized Decomposition applied to microwave processes involving multilayered components Article dans une revue avec comité de lectureTERTRAIS, Hermine; IBANEZ PINILLO, Ruben; BARASINSKI, Anais; GHNATIOS, Chady; CHINESTA, Francisco (Elsevier, 2019)Many electrical and structural components are constituted of a stacking of multiple thin layers with different electromagnetic, mechanical and thermal properties. When 3D descriptions become compulsory the approximation ...
Article dans une revue avec comité de lectureMARTÍN, Clara Argerich; MÉNDEZ, Arnulfo Carazo; SAINGES, Olivier; PETIOT, Emilie; BARASINSKI, Anais; PIANA, Mathieu; RATIER, Louis; CHINESTA, Francisco (MDPI, 2020)In the framework of civil aviation noise levels are becoming restricted every year, on one hand to provide comfort to the passengers and on the other hand to be compliant with regulations protecting airports surroundings. ...
Article dans une revue avec comité de lectureLEÓN, Angel; ARGERICH MARTÍN, Clara; BARASINSKI, Anaïs; SOCCARD, Eric; CHINESTA, Francisco (Springer Verlag, 2019)Automated tape placement - ATP - is a recent manufacturing technology for composite materials. Therefore, a correct modeling of the multi-physical process is critical in order to make possible in-situ consolidation. In ...
A novel sensitivity analysis on friction spot joining process performed on aluminum\polycarbonate sheets by simulation Article dans une revue avec comité de lectureSERRATORE, Giuseppe; GAGLIARDI, Francesco; MARTÍN, Clara Argerich; PINILO, Ruben Ibanez; CUETO, Elias; FILICE, Luigino; CHINESTA, Francisco (Springer Verlag, 2020)The manufacturing research has been focusing on the improvement of product performance and lightweight design. The synergic effects between material properties and manufacturing solutions have been considered, extensively. ...
Article dans une revue avec comité de lectureQUARANTA, Giacomo; ARGERICH MARTIN, Clara; IBÁÑEZ, Rubén; DUVAL, Jean Louis; CUETO, Elias; CHINESTA, Francisco (Elsevier Masson, 2019)The present paper analyzes different integration schemes of solid dynamics in the frequency domain involving the so-called Proper Generalized Decomposition – PGD. The last framework assumes for the solution a parametric ...