Support Vector Machine Regression for Concrete Compressive Strength Prediction

Support Vector Machine (SVM) is a generalized linear classifier that performs binary classification using supervised learning, with its decision boundary defined by the maximum-margin hyperplane derived from training samples. This implementation applies SVM regression to predict concrete compressive strength, featuring verified functionality and practical code implementation.

SVM Regression for Concrete Compressive Strength Prediction - Code Implementation and Analysis

Comprehensive code implementation with detailed explanations, fully tested and ready for deployment. Includes complete regression pipeline with data preprocessing, model training, and performance evaluation.

Support Vector Machine Regression for Concrete Compressive Strength Prediction

Support Vector Machine Regression Fitting - Concrete Compressive Strength Prediction with Implementation Details

BP Neural Network Implementation for Test Data Prediction

Implementation of BP Neural Network for Test Data Prediction with Code Integration