Supervised Learning
Supervised learning is concerned with models for predicting the outcome for new data points.
Models for supervised learning
The following supervised learning models are important:
- Linear models: models that assume the existence of a linear relationship between the independent variables and the outcome.
- Support vector machines: models that deal with non-linear associations by transforming the data to another space via kernel functions.
- Neural networks: models that emulate the interaction of neurons in the nervous system.
- \(k\)-nearest neighbors: a model that classifies a new data point according to its \(k\) nearest neighbors in the training data.
Posts on supervised learning
The following posts discuss the use of supervised learning in R.
