There are several methods have been categorized into three major groups including subspace search techniques, correlation-based clustering techniques, and biclustering techniques.Subspace Search Technique − A subspace search method searches several subspaces for clusters. Therefore, a cluster is a subset of objects that are the same as each other in a ... Read More

Active learning is a repetitive type of supervised learning that is relevant for situations where data are sufficient, but the class labels are scarce or costly to acquire. The learning algorithm is active in that it can carefully query a user (e.g., a person oracle) for labels. The multiple tuples ... Read More

The naıve Bayesian classifier makes the assumption of class conditional independence, i.e., given the class label of a tuple, the values of the attributes are assumed to be conditionally independent of one another. This simplifies computation.When the assumption influence true, therefore the naïve Bayesian classifier is the efficient in comparison ... Read More

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 ... Read More

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 ... Read More

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 ... Read More

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 ... Read More

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 ... Read More

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 ... Read More

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 ... Read More