CH6 - Machine Learning (ML) - Classification (Logistic Regression, KNN and Evaluate the performance)
In this Chapter:
Classification Problems
Logistic Regression (train by GD)
Sigmoid function
Maximum Likelihood Estimation (MLE)
KNN (k-nearest neighbors)
Evaluate the performance of a classification
Confusion Matrix
Accuracy
Precision
Recall
F1-Score
Area Under the ROC Curve (AUC-ROC)
Aim of this chapter:
Understanding two important Machine learning classification algorithms and learn how to evaluate the classification results.