The discriminant analysis approach relies on two main assumptions to appear at classification scores − First, it considers that the predictor measurements in some classes appear from a multivariate normal distribution. When this hypothesis is reasonably assembled, discriminant analysis is a dynamic tool than other classification methods, including logistic regression.It ... Read More

A k-nearest-neighbors algorithm is a classification approach that does not create assumptions about the structure of the relationship among the class membership (Y) and the predictors X1, X2, …. Xn.This is a nonparametric approach because it does not contain the estimation of parameters in a pretended function form, including the ... Read More

A k-nearest-neighbors algorithm is a classification approach that does not create assumptions about the structure of the relationship among the class membership (Y) and the predictors X1, X2, …. Xn.This is a nonparametric approach because it does not include estimation of parameters in a pretended function form, including the linear ... Read More

A frequent problem in data mining is that of utilizing a regression equation to forecast the value of a dependent variable when it can have several variables available to select as predictors in this model.Another consideration favoring the inclusions of numerous variables in the hope that a previously hidden relationship ... Read More

A heatmap is a graphical display of numerical data where color is used to denote values. In a data mining context, heatmaps are especially useful for two purposes − for visualizing correlation tables and for visualizing missing values in the data. In both cases, the information is conveyed in a ... Read More

Data Visualization defines the visual representation of data with the support of comprehensive charts, images, lists, charts, and multiple visual objects. It allows users to simply learn the data within a fraction of time and extract useful data, patterns, and trends. Furthermore, it creates the data simply to understand.In other ... Read More

Data mining is the process of finding useful new correlations, patterns, and trends by transferring through a high amount of data saved in repositories, using pattern recognition technologies including statistical and mathematical techniques. It is the analysis of factual datasets to discover unsuspected relationships and to summarize the records in ... Read More

Data mining is the process of finding useful new correlations, patterns, and trends by transferring through a high amount of data saved in repositories, using pattern recognition technologies including statistical and mathematical techniques. It is the analysis of factual datasets to discover unsuspected relationships and to summarize the records in ... Read More

Fact tables involve a composite primary key, which includes multiple foreign keys (one for each dimension table) and a column for each measure that uses these dimensions.Every data staging process must include a step for replacing the production IDs in the incoming fact table record with the data warehouse surrogate ... Read More

Data Warehousing is a technique that is mainly used to collect and manage data from various sources to give the business a meaningful business insight. A data warehouse is specifically designed to support management decisions.In simple terms, a data warehouse defines a database that is maintained independently from an organization’s ... Read More