1.3.2 Supervised Learning
Supervised learning is also known as directed learning. The learning process is directed by a previously known dependent attribute or target.
Supervised machine learning attempts to explain the behavior of the target as a function of a set of independent attributes or predictors. Supervised learning generally results in predictive models.
The building of a supervised model involves training, a process whereby the software analyzes many cases where the target value is already known. In the training process, the model "learns" the patterns in the data that enable making predictions. For example, a model that seeks to identify the customers who are likely to respond to a promotion must be trained by analyzing the characteristics of many customers who are known to have responded or not responded to a promotion in the past.
Oracle Machine Learning supports the following supervised machine learning functions:
Table 1-1 Supervised Machine Learning Functions
Function | Description | Sample Problem | Supported Algorithms |
---|---|---|---|
Feature Selection or Attribute Importance | Identifies the attributes that are most important in predicting a target attribute | Given customer response to an affinity card program, find the most significant predictors | |
Classification | Assigns items to discrete classes and predicts the class to which an item belongs | Given demographic data about a set of customers, predict customer response to an affinity card program | |
Regression | Approximates and forecasts continuous values | Given demographic and purchasing data about a set of customers, predict customers' age | |
Ranking | Predicts the probability of one item over other items | Recommend products to online customers based on their browsing history | XGBoost |
Time Series | Forecasts target value based on known history of target values taken at equally spaced points in time | Predict the length of the ocean waves, address tactical issues such as projecting costs, inventory requirements and customer satisfaction, and so on. | Exponential Smoothing |
Parent topic: Machine Learning Techniques and Algorithms