Assessment of compressive strength of eco-concrete reinforced using machine learning tools.

Predicting the compressive strength of Compressed Earth Blocks (CEB) is a challenging task due to the nonlinear relationships among their diverse components, including cement, clay, sand, silt, and fibers. This study employed PyCaret, an automated machine learning platform, to address this complexity by developing and evaluating predictive models. The analysis demonstrated that fiber content exhibited a strong positive correlation with cement content, with a correlation coefficient of 0.