## Bilatu

207-tik 1-10 emaitza erakusten

#### A Machine Learning Approach to Predict Healthcare Cost of Breast Cancer Patients

(Scientific Reports, Springer Nature, 2021)

This paper presents a novel machine learning approach to per- form an early prediction of the healthcare cost of breast cancer patients. The learning phase of our prediction method considers the following two steps: i) in ...

#### General supervision via probabilistic transformations

(Proceedings of the 24th European Conference on Artificial Intelligence-ECAI, 2020-08-01)

Different types of training data have led to numerous schemes for supervised classification. Current learning techniques are tailored to one specific scheme and cannot handle general ensembles of training samples. This ...

#### Advances on Time Series Analysis using Elastic Measures of Similarity

(2020-07-23)

A sequence is a collection of data instances arranged in a structured manner. When this arrangement is held in the time domain, sequences are instead referred to as time series. As such, each observation in a time series ...

#### Kernels of Mallows Models under the Hamming Distance for solving the Quadratic Assignment Problem

(Swarm and Evolutionary Computation, 2020-07)

The Quadratic Assignment Problem (QAP) is a well-known permutation-based combinatorial optimization problem with real applications in industrial and logistics environments. Motivated by the challenge that this NP-hard ...

#### Journey to the center of the linear ordering problem

(GECCO '20: Proceedings of the 2020 Genetic and Evolutionary Computation Conference, 2020-06)

A number of local search based algorithms have been designed to escape from the local optima, such as, iterated local search or variable neighborhood search. The neighborhood chosen for the local search as well as the ...

#### A General Framework for Prediction in Generalized Additive Models

(2020-01-13)

Smoothing techniques have become one of the most popular modelling approaches in the unidimensional and multidimensional setting. However, out-of-sample prediction in the context of smoothing models is still an open problem ...

#### Modelling species presence–absence in the ecological niche theory framework using shape-constrained generalized additive models

(Ecological Modelling, 2020-01-13)

According to ecological niche theory, species response curves are unimodal with respect to environmental
gradients. A variety of statistical methods have been developed for species distribution modelling. A general
problem ...

#### Mutual information based feature subset selection in multivariate time series classification

(Pattern Recognition, 2020)

This paper deals with supervised classification of multivariate time se- ries. In particular, the goal is to propose a filter method to select a subset of time series. Consequently, we adopt the framework proposed by Brown ...

#### in-depth analysis of SVM kernel learning and its components

(Neural Computing and Applications, 2020)

The performance of support vector machines in non-linearly-separable classification problems strongly relies on the kernel function. Towards an automatic machine learning approach for this technique, many research outputs ...

#### Optimization of deep learning precipitation models using categorical binary metrics

(Journal of Advances in Modeling Earth Systems, 2020)

This work introduces a methodology for optimizing neural network models using a combination of continuous and categorical binary indices in the context of precipitation forecasting. Probability of detection or false alarm ...