Other explorations might be aimed at sorting or classifying data, such as grouping prospective customers according to business attributes like industry, products, size, and location. A similar objective, outlier
we will see decision tree types based on the data mining problem. If we see about the decision tree, a decision tree is defined as that given a database D = {t1, t2,….tn} where ti denotes a tuple, which is defined by attributes set A = {A1, A2,…., Am}. Also, given a se...
If the business issue is being able to sell more – the data mining problem will be ‘what kind of customer is likely to make purchases of the product?’ The implementation begins with creating a model based on data such as earlier customer relations and attributes, including demographics, ...
More complex attributes then should be converted into binary tables. In our approach, called Generalized One-Sided Concept Lattices, we provide a method which deal with different types of attributes (e.g., ordinal, nominal, etc.) within one data table. Therefore, this method allows to create ...
In data mining, a decision tree is a description of data used for classification. For example, we can use a decision tree to determine whether an individual is likely to buy an item based on certain attributes such as income level and postal code....
The notion of a context is induced by the structure in the data set and has to be specified as a part of the problem formulation. Each data instance is defined using the following two sets of attributes: (1)Contextual attributes. The contextual attributes are used to determine the context ...
OLAP (Online Analytical Processing) is a computing method that enables users to easily and selectively extract and query data in order to analyze it from different points of view.
Data transformation has one simple goal -- to make data better and more useful for business tasks. When approached properly, a successful data transformation process can enhance various data attributes, including the following: Quality.Removing errors, duplicates, missing entries or gaps and improper ...
For example, sales activity and sales staff are two entities. Each of these entities has certain attributes. Some attributes of the sales activity entity might be which product was sold and by which account manager. The sales staff entity has a wholly separate set of attributes, some of which...
the more standard decision tree algorithms (C5.0 and C&RT) is that associations can exist between any of the attributes. A decision tree algorithm will build rules with only a single conclusion, whereas association algorithms attempt to find many rules, each of which may have a different ...