In this article, we will explain everything about finding the number of prime pairs in an array using C++. We have an array arr[] of integers, and we need to find all the possible prime pairs present in it. So here is the example for the problem −Input : arr[ ] = { 1, 2, 3, 5, 7, 9 } Output : 6 From the given array, prime pairs are (2, 3), (2, 5), (2, 7), (3, 5), (3, 7), (5, 7) Input : arr[] = {1, 4, 5, 9, 11} Output : 1Approaches to Find ... Read More
Interpolation is a method of generating a value between two given points on a line or a curve. In machine learning, interpolation is used to substitute the missing values in a dataset. This method of filling the missing values is called imputation. Another important use of interpolation is to smooth the discrete points in a dataset.SciPy provides us a module named scipy.interpolate having many functions with the help of which we can implement interpolation.ExampleIn the below example we will implement Interpolation by using the scipy.interpolate() package −First let’s generate some data to implement interpolation on that −import numpy as np ... Read More
Semi-supervised clustering is a method that partitions unlabeled data by creating the use of domain knowledge. It is generally expressed as pairwise constraints between instances or just as an additional set of labeled instances.The quality of unsupervised clustering can be essentially improved using some weak structure of supervision, for instance, in the form of pairwise constraints (i.e., pairs of objects labeled as belonging to similar or different clusters). Such a clustering procedure that depends on user feedback or guidance constraints is known as semisupervised clustering.There are several methods for semi-supervised clustering that can be divided into two classes which are ... Read More
Constraint-based clustering finds clusters that satisfy user-stated preferences or constraints. It is based on the nature of the constraints, constraint-based clustering can adopt instead of different approaches. There are several categories of constraints which are as follows −Constraints on individual objects − It can define constraints on the objects to be clustered. In a real estate application, for instance, one can like to spatially cluster only those luxury mansions worth over a million dollars. This constraint confines the collection of objects to be clustered. It can simply be managed by preprocessing (e.g., implementing selection using an SQL query), after which ... Read More
The determinant of a matrix, denoted by |A|, is a scalar value that can be calculated from a square matrix. With the help of the determinant of a matrix, we can find the inverse of a matrix and other things that are useful in the systems of linear equations, calculus, etc. The function named scipy.linalg.det() calculates the determinant of a square matrix.Let’s understand it with the below given examples −ExampleCalculating determinant of 2 by 2 matrix#Importing the scipy package import scipy #Importing the numpy package import numpy as np #Declaring the numpy array (Square Matrix) X = np.array([[5, ... Read More
SciPy has a function called scipy.linalg.solve() to solve linear equations. All we need to know is how we can represent our linear equation in terms of vectors. It will solve the linear equation set a * x = b for the unknown x. Let’s understand it with the help of below example −ExampleIn this example, we will be trying to solve a linear algebra system which can be given as follows − 3x + 2y = 2 x - y = 4 5y + z = -1The function scipy.linalg.solve() will find the values of x, y, and z for which ... Read More
Hamming distance calculates the distance between two binary vectors. Mostly we find the binary strings when we use one-hot encoding on categorical columns of data. In one-hot encoding the integer variable is removed and a new binary variable will be added for each unique integer value. For example, if a column had the categories say ‘Length’, ‘Width’, and ‘Breadth’. We might one-hot encode each example as a bitstring with one bit for each column as follows −Length = [1, 0, 0]Width = [0, 1, 0]Breadth = [0, 0, 1]The Hamming distance between any of the two categories mentioned above, can ... Read More
The EM (Expectation-Maximization) algorithm is a famous iterative refinement algorithm that can be used for discovering parameter estimates. It can be considered as an extension of the k-means paradigm, which creates an object to the cluster with which it is most similar, depending on the cluster mean.EM creates each object to a cluster according to a weight defining the probability of membership. In other term, there are no strict boundaries among clusters. Thus, new means are evaluated based on weighted measures.EM begins with an original estimate or “guess” of the parameters of the combination model (collectively defined as the parameter ... Read More
It is difficult to remember the values, units, and precisions of all physical constants. That’s the reason scipy.constants() have four methods with the help of which we can access physical constants. Let’s understand these methods along with examples −scipy.constants.value(key)− This method will give us the value in physical constants indexed by key.Parameterskey- It represents the key in dictionary physical_constants. Its value is a Python string or Unicode.Returnsvalue- It represents the value in physical_constants corresponding to the key parameter. Its value is of float type.Examplefrom scipy import constants constants.value(u'proton mass')Output1.67262192369e-27scipy.constants.unit(key)− This method will give us the unit in physical constants indexed ... Read More
To implement Scientific or Mathematical calculation, we need various universal constants. For example, the formula to calculate area of a circle is pi*r*r where Pi is a constant having value = 3.141592653. There are various other scenarios like this where we need constants. It would really be helpful if we can incorporate these constants into our calculation with ease. The scipy.constants(), a sub-module inside the Scipy library, does the job for us and provide us a reference material to look up exhaustive list of Physical Constants, universal mathematical constants, and various units such as SI prefixes, Binary prefixes, Mass, Angle, ... Read More
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