Usually, the comparison among genomic prediction models is based on validation schemes as Repeated Random Subsampling (RRS) or K-fold cross-validation. Nevertheless, design of training and sets has a high effect way subjectiveness we compare models. Those procedures cited above have an overlap across replicates that might cause overestimated estimate lack residuals independence due to resamplin...

Background: COVID-19 is a disease that attacks the respiratory system and highly contagious, so cases of spread are increasing every day. The increase in cannot be predicted accurately, resulting shortage services, facilities medical personnel. This number will always if community not vigilant actively reduces rate adding confirmed cases. Therefore, public awareness vigilance need to increased ...

This paper deals with the combination of classification models that have been derived from running different (heterogeneous) learning algorithms on the same data set. We focus on the Classifier Evaluation and Selection (ES) method, that evaluates each of the models (typically using 10-fold cross-validation) and selects the best one. We examine the performance of this method in comparison with t...

One of the most widely used standard procedures for model evaluation in classification and regression is K-fold cross-validation (CV). However, when it comes to time series forecasting, because of the inherent serial correlation and potential non-stationarity of the data, its application is not straightforward and often omitted by practitioners in favor of an out-of-sample (OOS) evaluation. In ...

an alumina supported co/ni catalyst was prepared by sol-gel procedure to study the catalytic behavior during fischer-tropsch synthesis in a fixed-bed reactor. the effect of co conversion (10-50%) on hydrocarbon product distribution (ch4, c5+ and c2-c4 olefin selectivities) was studied. selectivity for ch4 decreased, while those of c5+ and olefin selectivities increased with increasing co conver...

Traditional methods of detecting cardiac illness are often problematic in the medical field. The doctor must next study and interpret findings patient's record received from electrocardiogram echocardiogram. These tasks take a long time require patience. use computational technology medicine, especially disease, is not new. Scientists continuously striving for most reliable method diagnosing il...

In machine learning data usage is the most important criterion than logic of program. With very big and moderate sized datasets it possible to obtain robust high classification accuracies but not with small datasets. particular only large training are potential for producing decision tree results. The results obtained by using one testing dataset pair reliable. Cross validation technique uses m...