What is Discovery Driven Exploration

Ginni
Updated on 16-Feb-2022 11:06:07

1K+ Views

Discovery-driven exploration is such a cube exploration approach. In discovery-driven exploration, precomputed measures indicating data exceptions are used to guide the user in the data analysis process, at all levels of aggregation. It refer to these measures as exception indicators.Intuitively, an exception is a data cube cell value that is significantly different from the value anticipated, based on a statistical model. The model treated variations and patterns in the measure value across all of the dimensions to which a cell apply.For instance, if the analysis of item-sales data acknowledge an increase in sales in December in comparison to several months, ... Read More

Return Truncated Value of Array Elements in NumPy

AmitDiwan
Updated on 16-Feb-2022 11:03:34

2K+ Views

To return the truncated value of the array elements, use the numpy.trunc() method in Python Numpy. The function returns the truncated value of each element in x. This is a scalar if x is a scalar. The truncated value of the scalar x is the nearest integer i which is closer to zero than x is. In short, the fractional part of the signed number x is discarded.The out is a location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. ... Read More

Return the Floor of a Specific Array Element in NumPy

AmitDiwan
Updated on 16-Feb-2022 10:57:53

152 Views

To return the floor of a specific array element, use the index value in the numpy.floor() method in Python Numpy. The floor of the scalar x is the largest integer i, such that i

Return Lower Triangle of an Array and Set Diagonal to Zero in NumPy

AmitDiwan
Updated on 16-Feb-2022 10:53:06

358 Views

To return the lower triangle of an array, use the numpy.tril() method in Python Numpy −The 1st parameter is the input arrayThe 2nd parameter is the 'k' i.e. the diagonal above which to zero elements.k = 0 (the default) is the main diagonal, k 0 is above.The function returns a copy of an array with elements above the k-th diagonal zeroed. For arrays with ndim exceeding 2, tril will apply to the final two axes.StepsAt first, import the required library −import numpy as npCreate a 2d array −arr = np.array([[36, 36, 78, 88], [92, 81, 98, 45], [22, 67, ... Read More

Print an Integer in Java

AmitDiwan
Updated on 16-Feb-2022 10:51:46

7K+ Views

In this article, we will understand how to print an integer in Java. It uses the int data type. The int data type is a 32-bit signed two's complement integer. The Minimum value is 2, 147, 483, 648 (-2^31) and the Maximum 2, 147, 483, 647(inclusive) (2^31 -1). Integer is generally used as the default data type for integral values unless there is a concern about memory. The default value is 0.InputSuppose our input isEnter an integer: 45OutputThe desired output would beThe integer is: 45AlgorithmStep 1- START Step 2- Prompt the user to enter an integer value/ define the integer ... Read More

Create Array with Ones at and Below Diagonal in NumPy

AmitDiwan
Updated on 16-Feb-2022 10:49:03

127 Views

To create an array with ones at and below the given diagonal and zeros elsewhere, use the numpy.tri() method in Python NumpyThe 1st parameter is the number of rows in the arrayThe 2nd parameter is the number of columns in the arrayThe "type" parameter is used to set the type of the returned arrayThe tri() function returns an array with its lower triangle filled with ones and zero elsewhere; in other words T[i,j] == 1 for j

Create Array with Ones at and Below Diagonal in NumPy

AmitDiwan
Updated on 16-Feb-2022 10:45:35

392 Views

To create an array with ones at and below the given diagonal and zeros elsewhere, use the numpy.tri() method in Python Numpy −The 1st parameter is the number of rows in the arrayThe 2nd parameter is the number of columns in the arrayThe tri() function returns an array with its lower triangle filled with ones and zero elsewhere; in other words T[i,j] == 1 for j

Create Two-Dimensional Array with Flattened Input as Lower Diagonal in NumPy

AmitDiwan
Updated on 16-Feb-2022 10:41:35

160 Views

To create a two-dimensional array with the flattened input as a diagonal, use the numpy.diagflat() method in Python Numpy. The 'K parameter is used to set the diagonal; 0, the default, corresponds to the “main” diagonal, a negative k giving the number of the diagonal below the main.The first parameter is the input data, which is flattened and set as the k-th diagonal of the output. The second parameter is the diagonal to set; 0, the default, corresponds to the “main” diagonal, a positive (negative) k giving the number of the diagonal above (below) the main.NumPy offers comprehensive mathematical functions, ... Read More

Create Two-Dimensional Array with Flattened Input as Upper Diagonal in NumPy

AmitDiwan
Updated on 16-Feb-2022 10:37:53

193 Views

To create a two-dimensional array with the flattened input as a diagonal, use the numpy.diagflat() method in Python Numpy. The 'K parameter is used to set the diagonal; 0, the default, corresponds to the “main” diagonal, a positive (negative) k giving the number of the diagonal above (below) the main.The first parameter is the input data, which is flattened and set as the k-th diagonal of the output. The second parameter is the diagonal to set; 0, the default, corresponds to the “main” diagonal, a positive (negative) k giving the number of the diagonal above (below) the main.NumPy offers comprehensive ... Read More

Create Two-Dimensional Array with Flattened Input as Diagonal in NumPy

AmitDiwan
Updated on 16-Feb-2022 10:33:45

499 Views

To create a two-dimensional array with the flattened input as a diagonal, use the numpy.diagflat() method in Python Numpy. The first parameter is the input data, which is flattened and set as the kth diagonal of the output. The second parameter is the diagonal to set; 0, the default, corresponds to the “main” diagonal, a positive (negative) k giving the number of the diagonal above (below) the main.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

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