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Data Mining Articles
Page 5 of 36
How can the data be visualized to support interactive decision tree construction?
Perception-based classification (PBC) is an interactive method based on multidimensional visualization methods and enable the user to incorporate background knowledge about the data when constructing a decision tree.By optically interacting with the data, the user is likely to produce a deeper learning of the data. The resulting trees likely to be smaller than those construct utilizing traditional decision tree induction techniques and therefore are simpler to interpret, while achieving about the similar accuracy.PBC need a pixel-oriented method to consider multidimensional data with its class label data. The circle segments method is adapted, which maps d-dimensional information objects to a circle ...
Read MoreWhat are the Applications of Pattern Mining?
There are various applications of Pattern Mining which are as follows −Pattern mining is generally used for noise filtering and data cleaning as preprocessing in several data-intensive applications. It can be used to explore microarray data, for example, which includes tens of thousands of dimensions (e.g., describing genes).Pattern mining provides in the discovery of inherent mechanisms and clusters hidden in the data. Given the DBLP data set, for example, frequent pattern mining can simply discover interesting clusters like coauthor clusters (by determining authors who generally collaborate) and conference clusters (by determining the sharing of several authors and terms). Such architecture ...
Read MoreWhat are the techniques for Data Cube Computations?
The following are general optimization techniques for efficient computation of data cubes which as follows −Sorting, hashing, and grouping − Sorting, hashing, and grouping operations must be used to the dimension attributes to reorder and cluster associated tuples. In cube computation, aggregation is implemented on the tuples that share the similar set of dimension values. Therefore, it is essential to analyse sorting, hashing, and grouping services to access and group such data to support evaluation of such aggregates.It can calculate total sales by branch, day, and item. It can be more effective to sort tuples or cells by branch, and ...
Read MoreHow does data mining relate to information processing and online analytical processing?
There are three kinds of data warehouse applications such as information processing, analytical processing, and data mining.Information processing − It provides querying, basic numerical analysis, and documenting using crosstabs, tables, charts, or graphs. A modern trend in data warehouse data processing is to make low-cost web-based accessing tools that it is integrated with web browsers.Analytical processing − It provides basic OLAP operations, such as slice-and-dice, drilldown, roll-up, and pivoting. It usually works on historic information in both summarized and detailed forms. The major area of online analytical processing over information processing is the multidimensional information analysis of data warehouse data.Data ...
Read MoreHow are organizations using the information from data warehouses?
Data Warehousing is an approach that can collect and manage data from multiple sources to provide the business a significant business insight. A data warehouse is specifically designed to provide management decisions.In simple terms, a data warehouse defines a database that is maintained independently from an organization’s operational databases. Data warehouse systems enable the integration of multiple application systems. They support data processing by providing a solid platform of consolidated, historical data for analysis.A data warehouse is a semantically consistent data save that handle as a physical execution of a decision support data model. It saves the data an enterprise ...
Read MoreWhat are the methods for the generation of concept hierarchies for nominal data?
There are various methods for the generation of concept hierarchies for nominal data as follows −Specification of a partial ordering of attributes explicitly at the schema level by users or professionals − Concept hierarchies for nominal attributes or dimensions generally contains a set of attributes. A user or professionals can simply represent a concept hierarchy by defining a partial or total governing of the attributes at the schema level.For instance, suppose that a relational database includes the following set of attributes such as street, city, province or state, and country. A data warehouse location dimension can include the same attributes. ...
Read MoreWhat are the tasks in data preprocessing?
There are the major steps involved in data preprocessing, namely, data cleaning, data integration, data reduction, and data transformation as follows −Data Cleaning − Data cleaning routines operate to “clean” the information by filling in missing values, smoothing noisy information, identifying or eliminating outliers, and resolving deviation. If users understand the data are dirty, they are unlikely to trust the results of some data mining that has been used.Moreover, dirty data can make confusion for the mining phase, resulting in unstable output. Some mining routines have some phase for dealing with incomplete or noisy information, they are not always potent. ...
Read MoreWhat is an Attribute?
An attribute is a data field, defining a characteristic of a data object. The nouns attribute, dimension, feature, and variable are used correspondently in the literature. The dimension is generally used in data warehousing. Machine learning literature influence to use the term feature, while statisticians prefer the method svariable.Data mining and database experts generally use the term attribute. Attributes defining a user object can include, for instance, customer ID, name, and address. Observed values for a given attribute are referred to as observations.A set of attributes can define a given object is known as attribute vector (or feature vector). The ...
Read MoreWhat are the different aspects of mining methodology?
There are various aspects of mining methodology which are as follows −Mining various and new kinds of knowledge − Data mining covers a broad spectrum of data analysis and knowledge discovery services, from data characterization and discrimination to relations and correlation analysis, classification, regression, clustering, outlier methods, sequence methods, and trend and computational analysis.These services can use the same database in multiple ways and need the development of several data mining techniques. Because of the diversity of software, new mining services continue to emerge, developing data mining a powerful and fast-increasing field.For instance, for effective knowledge discovery in data networks, ...
Read MoreHow is the derived model presented in data mining?
Classification is the procedure of discovering a model that defines and categorize data classes or concepts. The model are based on the search of a set of training data (i.e., data objects for which the class labels are famous). The model can predict the class label of objects for which the class label is anonymous.The derived model can be represented in several forms, including classification rules (i.e., IF-THEN rules), decision trees, numerical formulae, or neural networks. A decision tree is a flowchart-like tree architecture, where each node indicates a test on an attribute value, each branch defines an outcome of ...
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