Supervised Learning Algorithms

Here’s What We’ll Cover:

Supervised Learning Algorithms

In supervised learning, algorithms are trained using labeled datasets, and they learn about each input category. We evaluate the approach using test data (a subset of the training set) and predict outcomes after completing the training phase. There are two types of supervised machine learning:

• Classification
• Regression

Classification vs Regression

• Regression: linear regression, logistic regression, polynomial regression.
• Classification: decision trees, random forests, support vector machines (SVM), k-nearest neighbors (KNN), naive Bayes.
• Model evaluation: accuracy, F1-score, ROC curve, confusion matrix.