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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 More
To return a copy of the string with all occurrences of substring old replaced by new, use the numpy.char.replace() method in Python Numpy −The 1st parameter is the input arrayThe 2nd parameter is the old string to be replacedThe 3rd parameter is the new string to be replaced with the oldIf the optional parameter count is given, only the first count occurrences are replacedThe numpy.char module provides a set of vectorized string operations for arrays of type numpy.str_ or numpy.bytes_.StepsAt first, import the required library −import numpy as npCreate an array −arr = np.array(["Welcome to the Jungle", "Jungle Safari"])Displaying our ... 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 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 More
To return a copy of an array with the trailing characters removed, use the numpy.char.rstrip() method in Python Numpy. The "chars" parameter is used to set a string specifying the set of characters to be removed. If omitted or None, the chars argument defaults to removing whitespace. The chars argument is not a prefix; rather, all combinations of its values are stripped.The numpy.char module provides a set of vectorized string operations for arrays of type numpy.str_ or numpy.bytes_.The chars parameter is a string specifying the set of characters to be removed. If omitted or None, the chars argument defaults to ... 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 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 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 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 More
To return True if two arrays are element-wise equal within a tolerance, use the ma.allclose() method in Python Numpy. This function is equivalent to allclose except that masked values are treated as equal (default) or unequal, depending on the masked_equal argument. The "masked_values" parameter is used to set the masked values in both the arrays are considered equal (True) or not (False).Returns True if the two arrays are equal within the given tolerance, False otherwise. If either array contains NaN, then False is returned.A masked array is the combination of a standard numpy.ndarray and a mask. A mask is either ... 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 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 More
To return a copy of an array with the trailing spaces removed, use the numpy.char.rstrip() method in Python Numpy.The numpy.char module provides a set of vectorized string operations for arrays of type numpy.str_ or numpy.bytes_.The chars parameter is a string specifying the set of characters to be removed. If omitted or None, the chars argument defaults to removing whitespace. The chars argument is not a suffix; rather, all combinations of its values are stripped.StepsAt first, import the required library −import numpy as npCreate a One-Dimensional array of string with some leading and trailing spaces −arr = np.array([' Tom ', ' ... Read More
DescriptionOut-GridView in a PowerShell is the output format in the GUI format. Generally, we get the output on the console using the Format-Table or Format-List command. Similarly, Out-GridView is also the output format but we can interact with it because of the GUI format.Moreover, it provides us options to select single or multiple rows and we can store the selected output and can utilize them in the script.Out-Gridview with PipelineYou can pipeline output to the Gridview in a similar way as Format-Table or Format-List commands.Example1 − With Pipeline outputGet-Service | where{$_.StartType -eq 'Disabled'} | Out-GridViewOutputThe above command will get all ... Read More