Machine Learning - (Supervised|Directed) Learning ("Training") (Problem)

> (Statistics|Probability|Machine Learning|Data Mining|Data and Knowledge Discovery|Pattern Recognition|Data Science|Data Analysis)

1 - About

Supervised Learning has the goal of predicting a value (outcome) from particular characteristics (predictors) that describes some behaviour.

The attribute used to trained and being predicted is called the Target (outcome, ...) attribute.

When the outcome attribute is:

Supervised learning is also known as directed learning. Directed data mining attempts to explain the behaviour of the target as a function of a set of independent attributes or predictors.

Supervised learning generally results in predictive models. This is in contrast to unsupervised learning where the goal is pattern detection.

The building of a supervised model involves training with a training data set of observations.

In supervised learning, you infer the general equation. For instance in linear regression, you infer the m and b of the equation y = bx+ m from the x and y


3 - Objectives