Data Structure
Networking
RDBMS
Operating System
Java
MS Excel
iOS
HTML
CSS
Android
Python
C Programming
C++
C#
MongoDB
MySQL
Javascript
PHP
The sequential exception technique simulates the method in which humans can distinguish unusual sets from between a sequence of supposedly like objects. It helps implicit redundancy of the data.Given a data set, D, of n objects, it construct a sequence of subsets, {D1, D2, ..., Dm}, of these objects with 2 ≤ m ≤ n including$$\mathrm{D_{j−1}\subset D_{j}\:\:where\: D_{j}\subseteq D}$$Dissimilarities are assessed between subsets in the series. The technique learns the following terms which are as follows −Exception set − This is the set of deviations or outliers. It is defined as the smallest subset of objects whose removal results in ... Read More
To shift the bits of an integer to the right, use the numpy.right_shift() method in Python Numpy. Bits are shifted to the right x2. Because the internal representation of numbers is in binary format, this operation is equivalent to dividing x1 by 2**x2.The x1 is the Input values. The x2 is the number of bits to remove at the right of x1. If x1.shape != x2.shape, they must be broadcastable to a common shape.The function right_shift() returns x1 with bits shifted x2 times to the right. This is a scalar if both x1 and x2 are scalars.StepsAt first, import the ... Read More
To compute the bit-wise XOR of two arrays element-wise, use the numpy.bitwise_xor() method in Python Numpy. Computes the bit-wise XOR of the underlying binary representation of the integers in the input arrays. This ufunc implements the C/Python operator ^.The 1st and 2nd parameter are the arrays, only integer and boolean types are handled. If x1.shape != x2.shape, they must be broadcastable to a common shape.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. ... Read More
To true divide each element of a masked Array by a scalar value in-place, use the ma.MaskedArray.__itruediv__() 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
To compute the bit-wise XOR of a 1D and a 2D array element-wise, use the numpy.bitwise_xor() method in Python Numpy.Computes the bit-wise XOR of the underlying binary representation of the integers in the input arrays. This ufunc implements the C/Python operator ^.The 1st and 2nd parameter are the arrays, only integer and boolean types are handled. If x1.shape != x2.shape, they must be broadcastable to a common shape.StepsAt first, import the required library −import numpy as npCreating two numpy arrays using the array() method. We have inserted elements of int type −arr1 = np.array([32, 95, 82, 69, 38, 49]) arr2 ... Read More
To add a scalar value with each element of a masked Array in-place, use the ma.MaskedArray.__iadd__() 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
A partitioning clustering method is desirable because it minimizes the distance among sets and their cluster centers. If it can choose the k-means method, a cluster center cannot be available given the existence of obstacles.For instance, the cluster can turn out to be in the center of a lake. In other words, the k-medoids method chooses an object inside the cluster as a center and thus guarantees that a problem cannot appear.At each time a new medoid is selected, the distance among each object and its newly selected cluster center has to be recalculated. Because there can be obstacles among ... Read More
To replace tab characters by a fixed tabsize in a string array, use the numpy.char.expandtabs() method in Python Numpy. The "tabsize" parameter is used to replace tabs with tabsize number of spaces. If not given defaults to 8 spaces.The function expandtabs() returns a copy of each string element where all tab characters are replaced by one or more spaces, depending on the current column and the given tabsize. The column number is reset to zero after each newline occurring in the string. This doesn’t understand other non-printing characters or escape sequences.The numpy.char module provides a set of vectorized string operations ... Read More
To return a copy of each string element where all tab characters are replaced by spaces, use the numpy.char.expandtabs() method in Python Numpy. We can also set the "tabsize" parameter i.e. replace tabs with tabsize number of spaces. If not given defaults to 8 spaces.The function expandtabs() returns a copy of each string element where all tab characters are replaced by one or more spaces, depending on the current column and the given tabsize. The column number is reset to zero after each newline occurring in the string. This doesn’t understand other non-printing characters or escape sequences.The numpy.char module provides ... Read More
PROCLUS stands for Projected Clustering. It is a usual dimension-reduction subspace clustering techniques. That is, rather than starting from individual-dimensional spaces, it begins by finding an original approximation of the clusters in the high-dimensional attribute area.Each dimension is created a weight for each cluster, and the refreshed weights are used in the next iteration to recreate the clusters. This leads to the exploration of dense areas in all subspaces of some convenient dimensionality and prevents the generation of a huge number of overlapped clusters in projected dimensions of lower dimensionality.PROCLUS discover the best group of medoids by a hill-climbing phase ... Read More