The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...
Recently, the French firm AVISIA, specialized in data and artificial intelligence, unveiled its prediction for the 2025 Ballon d'Or using the AVISIA Player Index. According to their model—built on a ...
Recently, the French firm AVISIA, specialized in data and artificial intelligence, unveiled its prediction for the 2025 Ballon d'Or using the AVISIA Player Index. According to their model—built on a ...
The handling of missing data in cognitive diagnostic assessment is an important issue. The Random Forest Threshold Imputation (RFTI) method proposed by You et al. in 2023 is specifically designed for ...
Thank you for this wonderful repo! I'm currently using emlearn to run a Random Forest classifier. I noticed that the generated code uses if-else conditions and return <class> statements to perform ...
This repository provides an efficient binary video classification pipeline using PyTorch, optimized for local GPU-enabled PCs. It includes preprocessing and model inference tools for classifying ...
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 ...
ABSTRACT: In this study, multi-source remote sensing data and machine learning algorithms were used to delineate the prospect area of remote sensing geological prospecting in eastern Botswana. Landsat ...
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