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: This study employs linear regression to enhance inventory management, integrating IoT-based data collection for real-time decision-making. By contrasting traditional heuristic models, the ...
Modern AI research requires mastering dozens of specialized tools and frameworks. AI Researchers spend more time debugging infrastructure than testing hypotheses — slowing the pace of scientific ...
Experimental - This project is still in development, and not ready for the prime time. A minimal, secure Python interpreter written in Rust for use by AI. Monty avoids the cost, latency, complexity ...
Broadcasting plays an important role in offshore information transmission because of its stability and long-distance propagation characteristics. To improve propagation prediction in the offshore ...
The rapid uptake of supervised machine learning (ML) in clinical prediction modelling, particularly for binary outcomes based on tabular data, has sparked debate about its comparative advantage over ...
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