This paper proposes a model for predicting salaries based on the 1994 Census Database to predict whether final salary is over 50 thousand dollars or not. In order do this, researchers will identify various factors that may influence wages and analyze their impact salary. To find most accurate model, use 32561 records, each containing 15 elements, apply three different machine learning algorithm...

Obtaining consensual solutions is an important issue in decision making processes. It depends on several factors such as experts’ opinions, principles, knowledge, experience, etc. In the literature we can find a considerable amount of consensus measurement from different research areas (from a Social Choice perspective: Alcalde-Unzu and Vorsatz [1], Alcantud, de Andrés Calle and Cascón [2] and ...

In biomedical analytics correlation is one of the major criteria for the characterization of similarities between measured data items. It is demonstrated how the formal derivative of Pearson correlation can be used for gradient-based optimization of data models. Firstly, individual data attributes can be rated according to their impact on pairwise data relationships, analogous to the variance m...

Pearson product-moment correlation coefficients are a wellpracticed quantification of linear dependence seen across many fields. When calculating a sample-based correlation coefficient, the accuracy of the estimation is dependent on the quality and quantity of the sample. Like all statistical models, these correlation coefficients can suffer from overfitting, which results in the representation...

Principal component analysis (PCA) guided clustering approach is widely used in high dimensional data to improve the efficiency of Kmeans cluster solutions. Typically, Pearson correlation is used in PCA to provide an eigenanalysis to obtain the associated components that account for most of the variations in the data. However, PCA based Pearson correlation can be sensitive on non-Gaussian distr...