auth principal

If you are knowledgeable, it will be useful, as follows:void Main (){var x = Dengebenxi.compute (11111, 12, 3);X.dump ();var y = Anyuefuxidaoqihuanben.compute (11111, 12, 3);Y.dump ();var z = yicixinghuanbenfuxi.compute (11111, 12, 3);Z.dump ();}public class Dengebenxi{Equal and principal methodpublic static list{var monthrate = (yearrate)/1200.0; Annual interest rate converted to monthly interest ratevar datalist = new listvar i = 0;var a = 0.0; Repa

Principal component analysis is performed using PCA classes in the Sklearn library.Import the library you want to use, and the direct PIP installation is OK.from sklearn.decomposition import PCAimport numpy as np # 如果使用numpy的array作为参数的数据结构就需要，其他type没试过是否可以import pandas as pd # 非必要The main input parameters of the PCA class are as follows: n_components: This parameter can help us specify the number of feature dimensions that you want the PCA to be r

Amp; lt ;? PhpnamespaceAppHttpControllers; useAuth; {code...} How does it verify the Auth facade? There is no database query, and no code is available .. Use Auth; use Illuminate\Routing\Controller;class AuthController extends Controller { /** * Handle an authentication attempt. * * @return Response */ public function authenticate() { if (

1.PCAUsage Scenario: Principal component analysis is a data dimensionality reduction that converts a large number of related variables into a small set of unrelated variables called principal components.Steps: Data preprocessing (guaranteed no missing values in the data) Select a factor model (whether PCA or EFA) Determine the number of principal

50-D, where low-dimensional data is used primarily to better visualize the behavior of the algorithm). Is our data set:These data have been preprocessed so that each feature has the same mean value (0) and variance.For ease of display, depending on the size of the value, we have applied one of three colors to each point, but the color is not used for the algorithm but for illustration only.The PCA algorithm will look for a low-dimensional space to project our data. It can be seen that the main

principal Component Analysis 1. Description of the problem In many fields of research and application, it is often necessary to make a large amount of observations on multiple variables that reflect things, and collect large amounts of data for analysis to find the law. Large-scale multivariate samples will undoubtedly provide rich information for research and application, but also to some extent increase the workload of data collection, more importan

1.PCA principlePrincipal component Analysis (Principal Component ANALYSIS,PCA) is a statistical method. An orthogonal transformation transforms a set of variables that may be related to a set of linearly unrelated variables, and the transformed set of variables is called the principal component.PCA algorithm:Implementation of the 2.PCAData set:64-D handwritten digital imagesCode:#Coding=utf-8ImportNumPy as

The algorithm code is as follows: /// /// The separation of fast sorting, that is, for a specified Principal Component X, locate the position I so that the left element of I is less than or equal to X, and the right side is greater than or equal to X./// /// /// /// /// Private int quicksortpartion (INT [] A, int P, int q){ Int thecount = Q-p + 1;// If there is only one element,-1 is returned, indicating no further division.If (thecount = 1){Return-1;

To do data structure in the course of information, mainly to look at the inverse matrix of knowledge. The Gaussian-approximate (Gauss-jordan) elimination method of the chosen principal element is used in many places, for example, to find the inverse matrix of a matrix, to solve a linear equation group (one of the steps of the LM algorithm), and so on. Its speed is not the fastest, but it is very stable (from the definition of the Internet: A calculati

This article mainly introduces the ThinkPHP permission authentication Auth instance. if you need it, you can refer to the following example code to thoroughly analyze the implementation principles and methods of ThinkPHP permission authentication Auth. the specific steps are as follows: Some SQL code of mysql database: -- Optimize Table structure for think_auth_group -- -------------------------- drop tab