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To multiply each element of a masked Array by a scalar value in-place, use the ma.MaskedArray.__imul__() method in Python Numpy. A masked array is the combination of a standard numpy.ndarray and a mask. A mask is either nomask, indicating that no value of the associated array is invalid, or an array of booleans that determines for each element of the associated array whether the value is valid or not.NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. It supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and ... Read More
GSP stands for Generalised Sequential Patterns. It is a sequential pattern mining method that was produced by Srikant and Agrawal in 1996. It is an expansion of their seminal algorithm for usual itemset mining, referred to as Apriori. GSP needs the downward-closure natures of sequential patterns and adopts a several-pass, students create-and-test approach.The algorithm is as follows. In the first scan of the database, it can discover some frequent items, i.e., those with minimum support. Each item yields a 1-event frequent sequence including that item. Each subsequent pass begins with a seed group of sequential patterns and the group of ... Read More
To subtract a scalar value from each element of a masked Array in-place, use the ma.MaskedArray.__isub__() method in Python Numpy.A masked array is the combination of a standard numpy.ndarray and a mask. A mask is either nomask, indicating that no value of the associated array is invalid, or an array of booleans that determines for each element of the associated array whether the value is valid or not.NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. It supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse ... Read More
To compute the bit-wise NOT of an array element-wise, use the numpy.bitwise_not() method in Python Numpy. Computes the bit-wise NOT of the underlying binary representation of the integers in the input arrays. This ufunc implements the C/Python operator ˜.The where parameter is the condition broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an uninitialized out array is created via the default out=None, locations within it where the condition is False will remain uninitialized.StepsAt first, import ... Read More
Sequential pattern mining is the mining of frequently appearing series events or subsequences as patterns. An instance of a sequential pattern is users who purchase a Canon digital camera are to purchase an HP color printer within a month.For retail information, sequential patterns are beneficial for shelf placement and promotions. This industry, and telecommunications and different businesses, can also use sequential patterns for targeted marketing, user retention, and several tasks.There are several areas in which sequential patterns can be used such as Web access pattern analysis, weather prediction, production processes, and web intrusion detection.Given a set of sequences, where each ... Read More
To return a copy of an array with the leading spaces removed, use the numpy.char.lstrip() method in Python Numpy. The function returns an output array of str or unicode, depending on input type.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 prefix; rather, all combinations of its values are stripped.StepsAt first, import the required library −import numpy as npCreate a One-Dimensional array ... Read More
STREAM is an individual-pass, constant element approximation algorithm that was produced for the k-medians problem. The k-medians problem is to cluster N data points into k clusters or groups such that the sum squared error (SSQ) between the points and the cluster center to which they are assigned is minimized. The idea is to assign similar points to the same cluster, where these points are dissimilar from points in other clusters.In the stream data model, data points can only be seen once, and memory and time are limited. It can implement high-quality clustering, the STREAM algorithm processes data streams in ... Read More
To right-justify elements of an array and set the characters to use for padding, use the numpy.char.rjust() method in Python Numpy. The "width" parameter is the length of the resulting strings. The "fillchar" parameter is the character to use for padding.The function returns an output array of str or unicode, depending on input type. 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 a One-Dimensional array of string −arr = np.array(['Tom', 'John', 'Kate', 'Amy', 'Brad']) Displaying our array −print("Array...", arr)Get the datatype −print("Array ... Read More
Data stream clustering is described as the clustering of data that appar continuously including telephone data, multimedia data, monetary transactions etc. Data stream clustering is generally treated as a streaming algorithm and the objective is, given a sequence of points, to make a best clustering of the stream, utilizing a small amount of memory and time.Some applications needed the automated clustering of such data into set based on their similarities. Examples contains applications for web intrusion detection, analyzing Web clickstreams, and stock market analysis.There are several dynamic methods for clustering static data sets clustering data streams places additional force on ... Read More
To return a string which is the concatenation of the strings in the sequence, use the numpy.char.join() method in Python Numpy. The 1st parameter is the separator array. The 2nd parameter is the sequence array. The function returns an output array of str or unicode, depending on input typesThe 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 a One-Dimensional array of string −arr = np.array(['Bella\tCio', 'Tom\tHanks', 'Monry\tHeist\tSeries']) Displaying our array −print("Array...", arr)Get the datatype −print("Array datatype...", arr.dtype) Get the dimensions of the Array ... Read More