Comparative Analysis of Supervised Classification Algorithms for Residential Water End Uses

Keyphrases

• Comparative Analysis 100%
• Supervised Classification Algorithm 100%
• Residential Water 100%
• Water End Use 100%
• Labeled Data 50%
• Execution Time 50%
• RF Model 50%
• NN Model 50%
• High Performance 25%
• Accurate Estimation 25%
• Computationally Efficient 25%
• Model Performance 25%
• Best Model 25%
• Synthetic Data 25%
• Logistic Regression 25%
• Number of Events 25%
• Classification Model 25%
• Faucet 25%
• Actual Conditions 25%
• Random Forest 25%
• Built Environment 25%
• Sustainable Water Management 25%
• Classification Task 25%
• Grid Search 25%
• Toilet 25%
• One-class Support Vector Machine (OCSVM) 25%
• Balanced Data 25%
• Metering System 25%
• F1 Score 25%
• Imbalanced Data 25%
• Conditional Generative Adversarial Network (cGAN) 25%
• Smart Water Metering 25%
• Supervised Machine Learning Classifiers 25%
• Neural Networks NN 25%
• Optimized Hyperparameters 25%
• Decision Tree-based Models 25%

Computer Science

• Classification Algorithm 100%
• Execution Time 100%
• Supervised Classification 100%
• Support Vector Machine 100%
• Comparative Analysis 100%
• Machine Learning 50%
• Synthetic Data 50%
• Neural Network 50%
• Support Vector Machine 50%
• Performance Model 50%
• Random Decision Forest 50%
• Classification Models 50%
• Classification Task 50%
• Logistic Regression 50%
• Decision Trees 50%
• Generative Adversarial Networks 50%
• Imbalanced Data 50%
• Labeled Data Set 50%