Confusion Matrix
Confusion Matrix in Machine Learning 1. Introduction to Confusion Matrix A Confusion Matrix is a performance evaluation metric used in classification problems. It helps to understand how well a machine….
Tag: Model Comparison
ROC Curve and AUC
ROC Curve and AUC in Machine Learning The ROC (Receiver Operating Characteristic) Curve and AUC (Area Under the Curve) are essential metrics for evaluating the performance of classification models, especially….
Model Evaluation Metrics (Accuracy, Precision, Recall, F1-Score)
Model Evaluation Metrics in Machine Learning Evaluating a machine learning model is crucial for ensuring its effectiveness. Model evaluation metrics provide a way to measure performance, compare models, and fine-tune….
Train-Test Split and Cross-Validation
Train-Test Split and Cross-Validation in Machine Learning In machine learning, evaluating the performance of a model is crucial to ensure it generalizes well to unseen data. Two widely used techniques….