Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac

This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe

    In data mining and machine learning methods, it is traditionally assumed that training data, test data, and the data that will be processed in the future, should have the same feature space distribution. This is a condition that will not happen in the real world. In order to overcome this challenge, domain adaptation-based methods are used. One of the existing challenges in domain adaptation-based methods is to select the most efficient features so that they can also show the most efficiency in the destination database. In this paper, a new feature selection method based on deep reinforcement learning is proposed. In the proposed method, in order to select the best and most appropriate features, the essential policies

The research seeks to achieve its goal of demonstrating the impact of applying banking governance variables on the financial performance of Islamic banks, and the independent research variables are represented by (X) by (the number of independent members in the board (X1), the number of directors in the board (X2), the number of committees emanating from the board ( X3), the percentage of shares owned by major shareholders in the board (X4), the number of members of the Sharia supervisory board (X5)), and the dependent variable (Y) is represented by (rate of return on assets (Y1), rate of return on equity (Y2)).

The research sample included (4) Islamic banks, namely (Iraqi Islamic Bank, National Islamic Bank, Jihan Islamic Bank,

In the analysis of multiple linear regression, the problem of multicollinearity and auto-correlation drew the attention of many researchers, and given the appearance of these two problems together and their bad effect on the estimation, some of the researchers found new methods to address these two problems together at the same time. In this research a comparison for the performance of the Principal Components Two Parameter estimator (PCTP) and The (r-k) class estimator and the r-(k,d) class estimator by conducting a simulation study and through the results and under the mean square error (MSE) criterion to find the best way to address the two problems together. The results showed that the r-(k,d) class estimator is the best esti

The study aimed to identify the self- compassion of the students as well as to identify the differences in the self- compassion according to the variables: sex - the academic specialization - Study level, the sample of the study of (200) students distributed equally by sex (male - female) Specialization (Scientific - Human) compassion. The results showed that there were no differences in the self- compassion according to the variables: gender, academic specialization, and Study level. In light of these results, the researcher Number of the recommendations and proposals

In this paper, we define two operators of summation and summation-integral of q-type in two dimensional spaces. Firstly, we study the convergence of these operators and then we prove Voronovskaya- type asymptotic formulas for these operators.

The Intelligence of the Child in Relation to some Variables

In this work a study and calculation of the normal approach between two bodies, spherical and rough flat surface, had been conducted by the aid of image processing technique. Four kinds of metals of different work hardening index had been used as a surface specimens and by capturing images of resolution of 0.006565 mm/pixel a good estimate of the normal approach may be obtained the compression tests had been done in strength of material laboratory in mechanical engineering department, a Monsanto tensometer had been used to conduct the indentation tests.
A light section measuring equipment microscope BK 70x50 was used to calculate the surface parameters of the texture profile like standard deviation of asperity peak heights, centre lin

Free vibration behavior was developed under the ratio of critical buckling temperature of laminated composite thin plates with the general elastic boundary condition. The equations of motion were found based on classical laminated plate theory (CLPT) while the solution functions consists of trigonometric function and a continuous function that is added to guarantee the sufficient smoother of the so-named remaining displacement function at the boundaries, in this research, a modified Fourier series were used, a generalized procedure solution was developed using Ritz method combined with the imaginary spring technique. The influences of many design parameters such as angles of layers, aspect ratio, thickness ratio, and ratio of initial in-