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Database Articles
Page 180 of 547
What are the types of statistical-based algorithms?
There are two types of statistical-based algorithms which are as follows −Regression − Regression issues deal with the evaluation of an output value located on input values. When utilized for classification, the input values are values from the database and the output values define the classes. Regression can be used to clarify classification issues, but it is used for different applications including forecasting. The elementary form of regression is simple linear regression that includes only one predictor and a prediction.Regression can be used to implement classification using two various methods which are as follows −Division − The data are divided ...
Read MoreWhat are the various Issues regarding Classification and Prediction in data mining?
There are the following pre-processing steps that can be used to the data to facilitate boost the accuracy, effectiveness, and scalability of the classification or prediction phase which are as follows −Data cleaning − This defines the pre-processing of data to eliminate or reduce noise by using smoothing methods and the operation of missing values (e.g., by restoring a missing value with the most generally appearing value for that attribute, or with the best probable value established on statistics). Although various classification algorithms have some structures for managing noisy or missing information, this step can support reducing confusion during learning.Relevance ...
Read MoreWhat is Data Classification?
Classification is a data mining approach used to forecast team membership for data instances. It is a two-step procedure. In the first step, a model is built defining a predetermined set of data classes or approaches. The model is developed by considering database tuples defined by attributes.Each tuple is considered to belong to a predefined class, as decided by one of the attributes, known as the class label attribute. In the framework of classification, data tuples are also defined as samples, examples, or objects. The data tuples analyzed to develop the model jointly form the training data set. The single ...
Read MoreWhat are Genetic Algorithms?
Genetic algorithms are mathematical structures using the procedure of genetic inheritance. They have been successfully used to a broad variety of analytic issues. Data mining can connect human understanding with automatic analysis of information to find a design or key relationships.Given a large database represented over several variables, the objective is to effectively find the most interesting design in the database. Genetic algorithms have been used to recognize interesting designs in some software. They generally are used in data mining to enhance the execution of other algorithms, such as decision tree algorithms, another association rule.Genetic algorithms needed a specific data ...
Read MoreWhat are the applications for Neural Networks?
A neural network is an array of algorithms that endeavors to identify fundamental relationships in a set of data through a process that mimics the techniques the human brain operates. In this sense, neural networks refer to systems of neurons, either organic or artificial.Neural networks are applicable in virtually every situation in which a relationship between the predictor variables (independents, inputs) and predicted variables (dependents, outputs) exists, even when that relationship is very complex and not easy to articulate in the usual terms of “correlations” or “differences between groups.”There are various applications of Neural Networks which are as follows −Detection ...
Read MoreWhat are the applications of Similarity Measures?
Similarity measures provide the framework on which some data mining decisions are based. Tasks including classification and clustering generally consider the existence of some similarity measure, while fields with poor techniques to evaluate similarity often find that searching information is a cumbersome function.There are several applications of similarity measures are as follows −Information Retrieval − The goal of information retrieval (IR) systems is to meet user’s needs. In another terms, a need is generally manifested in the form of a short textual query introduced in the text box of some search engine online. IR systems generally do not directly answer ...
Read MoreWhat are the advantages and disadvantages of data mining?
Advantages of Data MiningThe advantage of data mining are as follows −Marketing/RetailingData mining can help direct marketers by supporting them with useful and accurate trends about their users purchasing behavior. It is based on these trends, marketers can direct their marketing attention to their customers with more precision. For example, marketers of a software company may advertise their new software to consumers who have a lot of software purchasing history.Moreover, data mining can also help marketers in predicting which products their users can be interested in purchasing. Through this prediction, marketers can surprise their users and create the users shopping ...
Read MoreWhat is the architecture of data mining?
Data mining is the process of discovering meaningful new correlations, patterns, and trends by shifting through large amounts of data stored in repositories, using pattern recognition technologies as well as statistical and mathematical techniques. It is the analysis of observational datasets to find unsuspected relationships and to summarize the data in novel ways that are both understandable and useful to the data owner.It is the procedure of selection, exploration, and modeling of high quantities of information to find regularities or relations that are at first unknown to obtain clear and beneficial results for the owner of the database. Data mining ...
Read MoreWhat is the structure for On-Line Analytical Mining?
An OLAM server performs analytical mining in data cubes similarly to an OLAP server performs online analytical processing. An integrated OLAM and OLAP mechanism, where the OLAM and OLAP servers both accept user online queries (or commands) via a graphical user interface API and operate with the data cube in the data analysis via a cube API.A metadata directory can be used to instruct the access of the data cube. The data cube can be created by accessing and integrating multiple databases via an MDDB API and by filtering a data warehouse via a database API that can provide OLE ...
Read MoreDifference between ROLAP, MOLAP, and HOLAP?
Relational OLAP (ROLAP) serversThese are the intermediate servers that stand in among a relational back-end server and client front-end tools. They facilitate a relational or extended-relational DBMS to save and manage warehouse data, and OLAP middleware to provide the missing item.ROLAP servers involve optimization for each DBMS back end, implementation of aggregation navigation logic, and more tools and services. ROLAP technology tends to have higher scalability than MOLAP technology. The DSS server of Micro strategy, for instance, adopts the ROLAP techniques.ROLAP systems work generally from the data that resides in a relational database, where the base data and dimension tables ...
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