Learning from Data
Date Submitted: 03/10/2004 18:02:37
Learning From Data
1. Introduction
Learning tools can be divided into two groups: Theory driven and data driven. Theory-driven learning, often called hypothesis testing, attempts to substantiate or disprove preconceived ideas. Theory-driven learning tools require the user to specify most of the model based on prior knowledge and then test to see whether or not the model is valid. In contrast, data-driven learning tools automatically create the model based on patterns found in the data. This
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mining is the production of a model. A model can be descriptive or predictive. A descriptive model helps in understanding underlying processes or behavior. For example, an association model describes consumer behavior. A predictive model is an equation or set of rules that makes it possible to predict an unseen or unmeasured value (the dependent variable or output) from, other, known values (independent variables or input). The form of the equation or rules is sugges
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