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Articles on Trending Technologies
Technical articles with clear explanations and examples
What is Randomized Algorithms and Data Stream Management System in data mining?
Randomized Algorithms − Randomized algorithms in the form of random sampling and blueprint, are used to deal with large, high-dimensional data streams. The need of randomization leads to simpler and more effective algorithms in contrast to known deterministic algorithms.If a randomized algorithm continually returns the correct answer but the running times change, it is called a Las Vegas algorithm. In contrast, a Monte Carlo algorithm has bounds on the running time but cannot restore the true result. It can usually consider Monte Carlo algorithms. The importance of a randomized algorithm is simply as a probability distribution over a group of ...
Read MoreReturn the addresses of the data and mask areas of a masked array in Numpy
To return the addresses of the data and mask areas of a masked array, use the ma.MaskedArray.ids() 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 MoreReturn the user-readable string representation of a masked array in Numpy
To return the user-readable string representation of a masked array, use the ma.MaskedArray.__str__() method in Python Numpy. Returns str(self). 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 MoreXOR every element of a masked array by a given scalar value using __ixor__() in Numpy
To XOR every element of a masked array by a given scalar value, use the ma.MaskedArray.__ixor__() method in Python Numpy. Returns self^=value. 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, ...
Read MoreGet the mod of every element of a masked Array with a scalar value using __imod__() in Numpy
To get the mod of every element of a masked Array with a scalar value, use the ma.MaskedArray.__imod__() 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, ...
Read MoreWhat is Sequential Exception Technique?
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 MoreShift the bits of an integer to the right in Numpy
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 MoreCompute the bit-wise XOR of two Numpy arrays element-wise
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 MoreTrue Divide each element of a masked Array by a scalar value in-place in Numpy
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 MoreAdd a scalar value with each element of a masked Array in-place in Numpy
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 ...
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