Hybrid Quantum-Classical Algorithm for an Integrated Feature Selection and Logistic Regression Model
Abstract: Feature selection is a pivotal step in machine learning, aimed at reducing feature dimensionality and improving model performance. Conventional feature selection methods, typically framed as ...
Abstract: Fuzzy classification models are important for handling uncertainty and heterogeneity in high-dimensional data. Although recent fuzzy logistic regression approaches have demonstrated ...
Implement Logistic Regression in Python from Scratch ! In this video, we will implement Logistic Regression in Python from Scratch. We will not use any build in models, but we will understand the code ...
In forecasting economic time series, statistical models often need to be complemented with a process to impose various constraints in a smooth manner. Systematically imposing constraints and retaining ...
ABSTRACT: Introduction: Biopsy procedures represent an essential diagnostic tool in the management of oral lesions. This study aims to evaluate the knowledge, attitudes, and practices of dental ...
In recent years, a learning method for classifiers using tensor networks (TNs) has attracted attention. When constructing a classification function for high-dimensional data using a basis function ...
ABSTRACT: With the rapid growth of e-commerce and online transactions, e-commerce platforms face a critical challenge: predicting consumer behavior after purchase. This study aimed to forecast such ...
Given Shout’s business plan, it seems likely they will mount a new special edition Blu-ray of Monty Python and the Holy Grail. “Since the earliest days of the company, Shout has been dedicated to ...
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