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The scipy.cluster.vq()has two methods to implement k-means clustering namely kmeans() and kmeans2(). There is a significant difference in the working of both these methods. Let us understand it −scipy.cluster.vq.kmeans(obs, k_or_guess, iter=20, thresh=1e-05, check_finite=True)− The kmeans() method forms k clusters by performing k-means algorithm on a set of observation vectors. To determine the stability of the centroids, this method uses a threshold value to compare the change in average Euclidean distance between the observations and their corresponding centroids. The output of this method is a code book mapping centroid to codes and vice versa.scipy.cluster.vq.kmeans2(data, k, iter=10, thresh=1e-05, minit='random', missing='warn', check_finite=True)− The ... Read More
scipy.cluster.vq.kmeans2(data, k, iter=10, thresh=1e-05, minit='random', missing='warn', check_finite=True)− The kmeans2() method classify a set of observations vectors into k clusters by performing k-means algorithm. To check for convergence, the kmeans2() method does not use threshold values. It has additional parameters to decide the method of initialization of centroids, to handle empty clusters, and to validate if the input metrices contain only finite numbers or not.Below is given the detailed explanation of its parameters −Parametersdata− ndarrayIt is an ‘M’ by ‘N’ array of M observations in N dimension.k− int or ndarrayThis parameter represents the number of clusters to form and the centroids ... Read More
The scipy.cluster.vq.kmeans(obs, k_or_guess, iter=20, thresh=1e- 05, check_finite=True)method forms k clusters by performing a k-means algorithm on a set of observation vectors. To determine the stability of the centroids, this method uses a threshold value to compare the change in average Euclidean distance between the observations and their corresponding centroids. The output of this method is a code book mapping centroid to codes and vice versa.Below is given the detailed explanation of its parameters−Parametersobs− ndarrayIt is an ‘M’ by ‘N’ array where each row is an observation, and the columns are the features seen during each observation. Before using, these features ... Read More
In this article, we need to find a number of prefix sum which are prime numbers in a given array arr[ ] of positive integers and range query L, R, where L is the initial index value arr[ L ] for prefixsum[ ] array and R is the number of prefix sum we need to find.To fill the prefix sum array, we start with index L to index R and add the present value with the last element in the given array. So here is the Example for the problem −Input : arr[ ] = { 3, 5, 6, 2, ... Read More
Before implementing k-means algorithms, the scipy.cluster.vq.vq(obs, code_book, check_finite = True) used to assign codes to each observation from a code book. It first compares each observation vector in the ‘M’ by ‘N’ obs array with the centroids in the code book. Once compared, it assigns the code to the closest centroid. It requires unit variance features in the obs array, which we can achieve by passing them through the scipy.cluster.vq.whiten(obs, check_finite = True)function.ParametersBelow are given the parameters of the function scipy.cluster.vq.vq(obs, code_book, check_finite = True) −obs− ndarrayIt is an ‘M’ by ‘N’ array where each row is an observation, and ... Read More
In this article, we will explain how to solve the number of possible pairs of hypotenuse and area form a right-angled triangle in C++.We need to determine the number of all possible pairs of a hypotenuse and the area ( H, A ) to form a right-angled triangle with H as hypotenuse and A as Area.In this example − x = Base of Right Angled Triangle y = Height of Right Angled Triangle H = hypotenuse of Right Angled TriangleWe know Area of right angled triangle, A = ( x * ... Read More
A timer can only be cancelled after it is being scheduled. The Immediate class has an object for setImmediate() method and passes the same object to clearImmediate(), in case it wants to cancel the scheduled timer function.Scheduling TimersThis type of timers schedules the task to take place after a certain instant of time.setImmediate()setInterval()setTimeout()Cancelling TimersThis type of timers cancels the scheduled tasks which is set to take place.ClearImmediate()clearInterval()clearTimeout()1. clearImmediate() methodThis method clears the Immediate timer object that is created by the setImmediate() method.SyntaxclearImmediate( timer )Examplefilename - clearImmediate.js// clearImmediate() Example var timer = setImmediate(function A() { console.log("Timer set"); }); ... Read More
In an array, A pair a[i], a[j] is known as an inversion if a[i] > a[j] and i < j. We have two numbers N and k, and need to figure out how many possible permutations of the first N numbers end in a perfect K inversion. So here is the example −Input: N = 4, K = 1 Output: 3 Explanation: Permutation of the first N numbers in total : 1234, 1243, 1324 and 2134. With 1 inversion we have 1243, 1324 and 2134. Input : N = 3, K = 2 Output : 3 Explanation: Permutation of ... Read More
In this article, we will see how to integrate Redis Cache with Spring Boot. We will learn how we can configure Redis data inside the Spring boot cache.Let's look at the dependencies first that are required to import Redis into a Spring boot application.Dependencies// Adding spring-boot cache & redis dependencies org.springframework.boot spring-boot-starter-cache 2.4.3 org.springframework.boot spring-boot-starter-data-redis 2.4.3 ConfigurationAfter adding the Redis dependencies, you now need to perform some configuration so that it could be used in your project. Spring Boot will automatically configure a Redis-cache Manager but with default properties. We can ... Read More
As we all know, pentagons and hexagons are equally essential parts of football. These shapes fit together like a puzzle for forming a perfectly spherical shape. So here we have a football, in which we have to find the hexagons and pentagons.We will use the Euler characteristic to solve the problem easily. Euler characteristic is a number that works to describe a specific shape or structure of any topological space. So we can use it for calculating the number of Pentagons and Hexagons on the football.In Euler characteristics −chi(S) − Integer for a specific surface SF − facesG − GraphV ... Read More