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Articles on Trending Technologies
Technical articles with clear explanations and examples
Return a list of the words in the string using separator as the delimiter string in Numpy
To return a list of the words in the string using separator as the delimiter string, use the numpy.char.split() method in Python Numpy −The 1st parameter is the input arrayThe 2nd parameter is the separatorIf maxsplit parameter is given, at most maxsplit splits are done. The function split() returns an array of list objects.The 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(["Bella-Cio", "Brad-Pitt", "Katie-Perry"])Displaying our array −print("Array...", arr)Get the datatype −print("Array datatype...", arr.dtype) Get the dimensions of the ...
Read MoreHow 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 MoreReturn a copy of the string with all occurrences of substring old replaced by new in Numpy
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 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 MoreReturn True if two Numpy arrays are element-wise equal within a tolerance
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 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 MoreOut-GridView in PowerShell
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 ...
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