|
|
|
Vera Afreixo, Ana Helena Tavares, Vera Enes, Miguel Pinheiro, Leonor Rodrigues and Gabriela Moura
In this work, we aimed to establish a stable and accurate procedure with which to perform feature selection in datasets with a much higher number of predictors than individuals, as in genome-wide association studies. Due to the instability of feature sel...
ver más
|
|
|
|
|
|
|
Michael McCord, Daniel Lo, Peadar Davis, John McCord, Luc Hermans and Paul Bidanset
Prediction accuracy for mass appraisal purposes has evolved substantially over the last few decades, facilitated by the evolution in big data, data availability and open source software. Accompanying these advances, newer forms of geo-spatial approaches ...
ver más
|
|
|
|
|
|
|
Manisha Sanjay Sirsat, Paula Rodrigues Oblessuc and Ricardo S. Ramiro
Genomic Prediction (GP) is a powerful approach for inferring complex phenotypes from genetic markers. GP is critical for improving grain yield, particularly for staple crops such as wheat and rice, which are crucial to feeding the world. While machine le...
ver más
|
|
|
|
|
|
|
Innocent Mudhombo and Edmore Ranganai
Although the variable selection and regularization procedures have been extensively considered in the literature for the quantile regression (????)
(
Q
R
)
scenario via penalization, many such procedures fail to deal with data aberrations in the design ...
ver más
|
|
|
|
|
|
|
Alessandro Araldi
Over the last two decades, a growing number of works in urban studies have revealed how micro-retail distribution is significantly related to specific properties of the urban built environment. While a wide variety of urban form measures have been invest...
ver más
|
|
|
|
|
|
|
Dipankar Kumar and Satoshi Takewaka
Automatic and accurate shoreline position and intertidal foreshore slope detection are challenging and significantly important for coastal dynamics. In the present study, a time series shoreline position and intertidal foreshore slope have been automatic...
ver más
|
|
|
|
|
|
|
Vincenzo Del Giudice, Pierfrancesco De Paola, Fabiana Forte and Benedetto Manganelli
This paper experiments an artificial neural networks model with Bayesian approach on a small real estate sample. The output distribution has been calculated operating a numerical integration on the weights space with the Markov Chain Hybrid Monte Carlo M...
ver más
|
|
|
|
|
|
|
Brian D. Marx; Paul H.C. Eilers
Pág. 13 - 22
|
|
|
|
|
|
|
Peter C. Austin
Pág. 549 - 565
|
|
|
|
|
|
|
Kohler, M; Krzyzak, A
Pág. 3054 - 3058
|
|
|
|