how to round to nearest whole number

/*************************************** * ******************************** // 13. Design algorithm, find the nearest common parent node of any two nodes on the binary tree. If the complexity is O (n2), no score is obtained. *//************************************* ********************************** // There is a solution for offer, the sub-node has a pointer to the parent node. // each node to the root node is a linked list, and the first public node

(Python) (supervised) kNN-Nearest Neighbor Classification Algorithm Supervised kNN neighbor algorithms: (1) calculate the distance between a point and the current point in a dataset of known classes. (2) sort by ascending distance (3) Select k points with the minimum distance from the current point (4) determine the frequency of occurrence of the category of the first k points (5) return the category with the highest frequency of occurrence of the fir

This is a multi-Cross Tree, and then finds the nearest public single-parent node of two points. Is a typical LCA problem. This is one of the many solutions that have been thoroughly studied. Original solution: search from the root node. If the two nodes are located on both sides of a node, the node is the closest public single-parent node. Trajan offline algorithm: if the minimum single-parent node is recorded when two nodes are found for the first ti

The Write Program finds the closest common ancestor of the two nodes in a binary tree. This question is discussed in two cases: In the first case, the node does not have a pointer to the parent node. In the second case, there is a pointer to the parent node. Let's first look at the first case. The node does not have a pointer to the parent node. We can use brute force to search for each node. If there are two known nodes, we can continue searching along the left and right subtree. If the tree

Question connection http://poj.org/problem? Id = 1330 Is to build a tree and then ask who is the closest public parent node between the two nodes? Code: 1/* Source Code 2 problem: 1330 User: huifeidmeng 3 memory: 1232 K time: 63 MS 4 Language: C ++ result: accepted 5 6 Source Code 7 */8 # include Poj ---- 1330 nearest common ancestors (simple LCA)

Introduction to AlgorithmsThe KNN algorithm principle is that there is a collection of sample data (the training sample set), and each data in the sample collection is known to classify the data. When we enter new data without a label, we compare the characteristics of the new data with the known sample collection, extracting the labels of the most closely related data, the label of the new data, and the classification calculation. Here we perform an abstract calculation based on the Euclidean d

The first question is the choice of K-value? How to quickly find a K-neighbor, especially if the feature space dimension is large and the training data capacity is large. (1) K-value problem: When the K value is very small, it is equivalent to a small field of training examples to predict, the approximate error of learning will be reduced, only the training instance closer to the input instance will work on the predicted results (in turn, the closer you are, the more similar, the farther aw

Topic Link: Click to open the linkTest instructions4 points on a given two-dimensional coordinateAsk:Find a point to make this point distance from 4 points and the minimumOutput distance and.Ideas:If 4 points are not convex 4-edged. Must be the optimal endpoint.Otherwise, the intersection of 2 diagonal lines is optimal, can be simply proved.For a convex 4-edged shape, sort the first corner.#include Uvalive 5102 Fermat Point in quadrangle Polar Sort + find distance two-dimensional coordinates 4 p

Question one:>>>import matplotlibNo module named ' Matplotlib ' appearsResolution process>pip Install MatplotlibAppearAfter the PIP version upgrade is imported matplotlib, the situation still occursSelect the 2.7.14 version of Project interpreter in Pycharm and install the Matplotlib package in itAfter the installation is successful, the import matplotlib appears in CMD.Thus problem one is solved.Question two:The name ' array ' is not definedWorkaround>>>from NumPy Import *The array is then impo

= \arg \min \alpha ' L\alpha \\\\. S.T (i) \alpha (i) where S S is a manually labeled region, S (i) s (i) is the pixel value in S. Use the following formula to solve: The main contribution of the (l+λd) ∑inαi=λm (L+\lambda D) \sum\limits_{i}^{n}\alpha_i=\lambda m K nearest neighbor is to propose a method of calculating Laplace matrix based on KNN. 1. Eigenvector calculation The eigenvector of a given pixel I is defined as follows: X (i) = (cos

A * Road algorithm principle can refer to this article, has been written in detail http://www.cppblog.com/mythit/archive/2009/04/19/80492.aspx This article mainly writes the real time collision which the multiple people seeks the road First talk about how to move the nearest point to the destination without finding a way In fact, all the points can be reached in the "close list", when all the points in the open list are traversed, if the end has not b

KNN algorithm belongs to supervised learning algorithm, which is a very simple algorithm for classification. Simply put, the KNN algorithm uses the method of measuring the distance between different eigenvalues to classify. The specific algorithm is as follows: 1 calculate the distance between the point in the known category DataSet and the current point 2) sorted by distance increment order 3 Select the K point with the current minimum distance 4 to determine the frequency of the category where

Introduction to K-Proximity algorithm: K-Neighbor algorithm is to calculate the distance between the data to be classified and the sample data, get the first k (usually not more than 20) and the most similar data to be classified data, then classify the K data, and classify the data to the category with the most occurrences. It is to be noted that 1, sometimes need to be based on the characteristics of the data in the classification of contribution size, weighted; 2, if the characteristics of th

The sword refers to the last question on offer, and a recursive function has been tuned for an afternoon to get the correct result. Topic Description: Given a tree, it also gives two nodes in the tree, and asks for their lowest common ancestor. Input: The input may contain more than one test sample. For each test case, the first behavior of the input is a number n (0 Each test sample includes two rows, the first behavior a first sequence travers

Program Listing One:from numpy import *import operatordef creatdataset (): group = Array ([[1.0,1.1], [1.0,1.0],[0,0],[0,0.1]]) labels = ["A", "a", "B", "B"] return group,labels def classify0 (inx,dataset,labels,k): Datasetsize = dataset.shape[0] Diffmat = Tile (InX, (datasetsize,1))-DataSet Sqdiffmat = diffmat**2 Sqdistanc es = sqdiffmat.sum (axis = 1) distances = sqdistances **0.5 Sorteddistindicis = Distances.argsort () print (sorte Ddistindicis) ClassCount = {} for I in range (k): Voteil

#include Stay in communication"Find out the distance in the plane of your nearest enemy" without calculating the distance

Finding the closest common ancestor of two nodes on the tree Algorithm 1: Tarjan LCA (u ){Make-set (u)Ancestor [find-set (u)] = u // sets the ancestor of the set where u is locatedV {LCA (V)Union (v, u) // merge the subset generated by V into U.Ancestor [find-set (u)] = u // prevents the change of the Set root (Representative) of U by means of tree-like heuristic combination.}Checked [u] = trueFor each (u, v) belongs to P {If checked [v] = trueThe nearest