Binary Classification and Regression in Machine Learning Overview This project focuses on implementing machine learning models for two key tasks: Binary Classification: Predicting categorical outcomes ...

ABSTRACT: The Efficient Market Hypothesis postulates that stock prices are unpredictable and complex, so they are challenging to forecast. However, this study demonstrates that it is possible to ...

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Abstract: The research entails the acquisition of live data from electrical systems, including measurements of voltage, current, and temperature. The use of feature engineering is implemented in order ...

Abstract: The paper bases on the theory of deep learning, uses the Scikit-learn machine learning framework and logistic regression algorithm, combines with supervised machine learning. Through Fourier ...

ABSTRACT: Over the past ten years, there has been an increase in cardiovascular disease, one of the most dangerous types of disease. However, cardiovascular detection is a technique that analyzes data ...

Introduction: Sequencing and phylogenetic classification have become a common task in human and animal diagnostic laboratories. It is routine to sequence pathogens to identify genetic variations of ...