Linear and non-linear classifiers

Type of course:

Digital learning, Lesson

Language:

Duration:

30 minutes

Workload:

2 hours

Proficiency:

Advanced

Target:

Manager, Professionals, Workers

This nugget introduces linear and non-linear classifiers, which are fundamental tools for classification tasks in various fields such as finance, healthcare, and marketing.You’ll learn about linear classifiers, such as logistic regression and linear discriminant analysis, which are efficient and interpretable techniques for modeling linear decision boundaries. Additionally, you’ll explore non-linear classifiers, including decision trees, support vector machines, and artificial neural networks, which can capture complex relationships between predictors and outcomes.

Learning outcomes

At the end of this nugget, the student will be able to apply linear classification techniques, such as logistic regression or linear discriminant analysis, to classify data using a linear separator.
At the end of this nugget, the student will be able to evaluate the accuracy of the model by comparing predicted values with actual values and calculate the misclassification rate.
At the end of this nugget, the student will be able to apply non-linear classification techniques, such as decision trees, artificial neural networks, or kernel methods, to classify data using a non-linear separator.