Learning Outcomes Express why Statistical Learning is important and how it can be used. Identify the strengths, weaknesses and caveats of different models and choose the most appropriate model for a ...

This week we will learn about non-parametric models. k-Nearest Neighbors makes sense on an intuitive level. Decision trees are a supervised learning model that can be used for either regression or ...

The course gives a good basis for further studies in statistics or Data Science, but is also useful for students who need to perform data analysis in other fields. Learning outcome. After completing ...

This paper presents a unified, efficient model of random decision forests which can be applied to a number of machine learning, computer vision and medical image analysis tasks. Our model extends ...

Learning Vector Quantization, aka LVQ (for both classification and regression) Support Vector Machines, aka SVM (for binary classification) Random Forests, a type of “bagging” ensemble ...

This review presents a unified, efficient model of random decision forests which can be applied to a number of machine learning, computer vision, and medical image analysis tasks. Our model extends ...