The core of big data models lies in the synergy of algorithm innovation, computational power support, and data governance to ...

Summary: This project focuses on supervised learning, particularly linear models, regularization techniques, overfitting, underfitting, and metrics for quality estimation. 💡 Tap here to leave your ...

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In this work, we perform a comparison analysis among linear regression, logistic regression, and all commonly used decision-tree-based methods, including Decision Trees (CART), Random Forests, and ...

Prediction model is used to forecast or predict value from dataset. But one of the most common problems in training prediction model is there are missing values in datasets. Problem is usually managed ...