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To understand various components of a machine learning algorithm, we first understand the definition of machine learning given by Professor Mitchell −“A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E.”As we can see the above definition, the main components of any machine learning algorithm are Task(T), Performance(P), and Experience(E).Based on these three components, let’s simplify the definition of machine learning −Machine learning is a subset of Artificial Intelligence (AI) and a field ... Read More
There are n number of intermediate train stations between point X and Y. Count the number of different ways trains can be arranged to stop at s stations such that no two stations are next to each other. So in this article, we will explain every possible approach to find out the number of stopping stations. Looking at the problem, we can find that we need to find combinations by which trains can be stopped at s number of stations.Approaches to Solve the ProblemLet's take an example that there are eight intermediate stations and we need to find the ways ... Read More
Do you know how much data a person is creating every second? The numbers are astonishing. According to Domo, during 2020 every person created 1.7MB of data every second and it is not going to slow down in the future as well. It would not be wrong to say that we are living in the 'age of data'. One of the biggest challenges in front of businesses and organizations is to make sense of all the data. They are trying to deal with it by creating intelligent systems using the concepts and methodologies from Machine Learning (ML), one of the ... Read More
The linear function named scipy.linalg.solve_toeplitz is used to solve the Toeplitz matrix equation. The form of this function is as follows −scipy.linalg.solve_toeplitz(c_or_cr, b, check_finite=True)This linear function will solve the equation Tx = b for x where T is the Toeplitz matrix.ParametersBelow are given the parameters of the function scipy.linalg.solve_toeplitz()c_or_cr− array_like or tuple of (array_like, array_like)This parameter is the vector c or tuple of arrays (c, r). Despite the actual shape of c, it will always be converted to a one-dimensional array. If r is not given, the assumption made is r = conjugate(c). Below are given two cases − ... Read More
In this article we are going to find number of solution of equation n = x + n ⊕ x, i.e we need to find number of values of x possible with given value n such that n = x + n ⊕ x where ⊕ represents XOR operation.Now we will discuss the complete information regarding number of solutions of n = x + n ⊕ x with an appropriate examples.Brute Force MethodWe can simple use brute force approach in order to find number of solution, i.e for given value of n we apply every integer value of x starting ... Read More
In this article, we will explain the approaches to find the number of solutions for the equation x+y+z
The linear function named scipy.linalg.solve_triangular is used to solve the triangular matrix e8quation. The form of this function is as follows −scipy.linalg.solve_triangular(a, b, trans=0, lower=False, unit_diagonal=False, overwrite_b=False, debug=None, check_finite=True)This linear function will solve the equation ax = b for x where a is a triangular matrix.P ParametersBelow are given the parameters of the function scipy.linalg.solve_triangular() −a− (M, M) array_likeThis parameter represents the triangular matrix.b− (M, ) or (M, N)array_likeThis parameter represents the right-hand side matrix in the equation ax = b.lower− bool, optionalBy using this parameter, we will be able to use only the data that is contained in the ... Read More
In this article, we will describe the important information on solving the number of sinks nodes in a graph. We have a Directed Acyclic Graph with N nodes (1 to N) and M edges in this problem. The goal is to find how many sink nodes are there in the given graph. A sink node is a node that does not produce any outgoing edges. So here is a simple example −Input : n = 4, m = 2 Edges[] = {{2, 3}, {4, 3}} Output : 2Simple Approach to Find the SolutionIn this approach, we will go through ... Read More
In this article, we will provide complete information to determine the number of siblings of a given node in the n-ary tree. We need to find the node's siblings with the value of key as given by the user; if it is non, then output as -1. There is only one approach that we can use −Simple ApproachIn this approach, we will go through all the nodes and check if a child has the same value as the user. If it exists, we answer a number of children - 1(the given value).Example #include using namespace std; class Node { ... Read More
The linear function named scipy.linalg.solveh_banded is used to solve the banded matrix equation. In the below given example we will be solving the circulant system Cx = b −Examplefrom scipy.linalg import solve_circulant, solve, circulant, lstsq import numpy as np c = np.array([2, 2, 4]) b = np.array([1, 2, 3]) solve_circulant(c, b)Output array([ 0.75, -0.25, 0.25])ExampleLet’s see a singular example, it will raise an LinAlgError −from scipy.linalg import solve_circulant, solve, circulant, lstsq import numpy as np c = np.array([1, 1, 0, 0]) b = np.array([1, 2, 3, 4]) solve_circulant(c, b)Output -------------------------------------------------------------------------- LinAlgError Traceback (most recent call last) in ... Read More