Samankaltainen aineisto
Näytetään aineistoja, joilla on samankaltainen nimeke tai asiasanat.
-
Problem Transformation Methods with Distance-Based Learning for Multi-Target Regression
Hämäläinen, Joonas; Kärkkäinen, Tommi (ESANN, 2020)Multi-target regression is a special subset of supervised machine learning problems. Problem transformation methods are used in the field to improve the performance of basic methods. The purpose of this article is to test ... -
On the Role of Taylor’s Formula in Machine Learning
Kärkkäinen, Tommi (Springer, 2023)The classical Taylor’s formula is an elementary tool in mathematical analysis and function approximation. Its role in the optimization theory, whose data-driven variants have a central role in machine learning training ... -
Do Randomized Algorithms Improve the Efficiency of Minimal Learning Machine?
Linja, Joakim; Hämäläinen, Joonas; Nieminen, Paavo; Kärkkäinen, Tommi (MDPI AG, 2020)Minimal Learning Machine (MLM) is a recently popularized supervised learning method, which is composed of distance-regression and multilateration steps. The computational complexity of MLM is dominated by the solution of ... -
Feature selection for distance-based regression : An umbrella review and a one-shot wrapper
Linja, Joakim; Hämäläinen, Joonas; Nieminen, Paavo; Kärkkäinen, Tommi (Elsevier, 2023)Feature selection (FS) may improve the performance, cost-efficiency, and understandability of supervised machine learning models. In this paper, FS for the recently introduced distance-based supervised machine learning ... -
Generation of Error Indicators for Partial Differential Equations by Machine Learning Methods
Muzalevskiy, Alexey; Neittaanmäki, Pekka; Repin, Sergey (Springer, 2022)Computer simulation methods for models based on partial differential equations usually apply adaptive strategies that generate sequences of approximations for consequently refined meshes. In this process, error indicators ...
Ellei toisin mainittu, julkisesti saatavilla olevia JYX-metatietoja (poislukien tiivistelmät) saa vapaasti uudelleenkäyttää CC0-lisenssillä.