Kernel-based learning algorithms have recently become the state-of-the-art machine learning methods of which the support vector machines are the most popular ones. Regularized least-squares (RLS), another kernel-based learning algorithm that is also known as the least-squares support vector machine, is shown to have a performance comparable to that of the support vector machines in several mach...

Physical inactivity is identified by the World Health Organization as the fourth leading risk factor for global mortality as it increases the risk of various adverse health conditions. App-based health interventions promise to help increase physical activity levels by enhancing the motivation of the users to exercise on a regular basis. One such app-based intervention which sends tailored coach...

estimation of the conceptual costs in construction projects can be regarded as an important issue in feasibility studies. this estimation has a major impact on the success of construction projects. indeed, this estimation supports the required information that can be employed in cost management and budgeting of these projects. the purpose of this paper is to introduce an intelligent model to im...

The quantitative structure property relationship (QSPR) for supercooled liquid vapour pressures (pL) of polybrominated diphenyl ethers (PBDEs) was investigated. The molecular distance–edge vector (MDEV) index was used as the structural descriptor. The quantitative relationship between the MDEV index and log pL was modelled by multivariate linear regression (MLR) and an artificial neural network...

BACKGROUND We address the problem of selecting and assessing classification and regression models using cross-validation. Current state-of-the-art methods can yield models with high variance, rendering them unsuitable for a number of practical applications including QSAR. In this paper we describe and evaluate best practices which improve reliability and increase confidence in selected models. ...

This paper studies V -fold cross-validation for model selection in least-squares density estimation. The goal is to provide theoretical grounds for choosing V in order to minimize the least-squares risk of the selected estimator. We first prove a non asymptotic oracle inequality for V -fold cross-validation and its bias-corrected version (V -fold penalization), with an upper bound decreasing as...

Streamflow forecasting has an important role in water resource management (e.g. flood control, drought management, reservoir design, etc.). In this paper, the application of Adaptive Neuro Fuzzy Inference System (ANFIS) is used for long-term streamflow forecasting (monthly, seasonal) and moreover, cross-validation method (K-fold) is investigated to evaluate test-training data in the model.Then,...

We evaluate the performance of weakestlink pruning of decision trees using crossvalidation. This technique maps tree pruning into a problem of tree selection: Find the best (i.e. the right-sized) tree, from a set of trees ranging in size from the unpruned tree to a null tree. For samples with at least 200 cases, extensive empirical evidence supports the following conclusions relative to tree se...

Cholesterol ratios (total cholesterol (TC)/high-density lipoprotein cholesterol (HDL-c) and triglyceride (TG)/HDL-c) have been suggested as better indicators to predict various clinical features such as insulin resistance and heart disease. Therefore, we aimed to build a single nucleotide polymorphism (SNP) set to predict constitutional lipid metabolism. The genotype data of 7795 samples were o...