Competent employees are a rare commodity for great companies. The problem of maintaining good with experience threatens the owners issue employee attrition can cost employers lot as it takes to compensate their expertise and efficiency. For this reason, in research, we present an automated model that predict based on different predictive analytical techniques. These techniques have been applied pipeline architectures select best champion model. Also, autotuning approach has implemented...

Abstract Accurate stock price forecasting is essential for making smart investing choices. In the context of Egyptian market, this study examines predictive capabilities several machine learning and deep models prediction. Five different datasets with historical information from significant companies are used in methods such as Random Forest, Linear Regression, LSTM, Bi-LSTM which were employed evaluated using performance metrics including Mean Squared Error (MSE), Absolute (MAE), R-Squared....

The spread of data on the web has increased in last twenty years. One reasons is appearance social media. sites describe many real-life events our daily lives. In period COVID-19 pandemic, a lot people and media organizations were writing documenting their health status latest news about coronavirus Using these tweets (sentiments) analyzing them computational model can help decision makers measuring public opinion yielding remarkable findings. this research article, we introduce deep...

Diabetes is a long-term disease. Inappropriate blood sugar level control in diabetic patients can lead to serious issues like kidney and heart diseases. Obesity widely regarded as major risk factor for type 2 diabetes. In this research, model proposed predict obese based on Expectation Maximization, PCA, SMOTE Algorithms the preprocessing feature extraction phases, using Fuzzy KNN classifier prediction phase. The applied real dataset accuracy of results reflects positive effect techniques....

A critical sum of data is often found, as it were, in the unstructured portion patient accounts Electronic Health Records (EHRs), making hard to handle and use for tasks such evidence-based health care or medical research. The proposed method uses a novel tool annotation text. This based on IBM Watson Platform UMLS source expressions their classifications; experiments are applied 100 documents collected from MIMIC set. results obtained promising this area research we precision recall value...

The unequal representation of the various divisions existing in data is one main inconsistency issues.Data with an imbalanced distribution negatively influence efficiency most conventional classifiers.This paper introduces a new method for over-sampling handling sets.The hybridize chicken swarm optimization and fuzzy logic (CSO-FL).The proposed model ensures that synthetic samples generated reside minority regions.The hybrid CSO-FL applied on three datasets different ratios between 1.78...

The graduates who have finished their study program will be given a merit award and certificates graded in accordance with the degree of academic accomplishment. awards are generally offered using two methods; one is by cumulative grade point average (CGPA) other percentage all marks for students. problem when assigning course final grade; each student's translated to letter, allowing discrepancy within same letter range ranking. If students score, that means equal results. However, this...

Motor defects are a major problem affecting millions of people around the world. These individuals suffer from weakness in day-to-day functioning, which can lead to decreased and incoherent daily routines impair their quality life. This research describes new machine learning-based model intended help with limb motor disabilities using brain signals control assistive devices life activities. The proposed uses Empirical Mode Decomposition for removing artifacts electroencephalography (EEG)...