eig sitebuilder

image, (I = 1, 2... c; j = 1, 2 ..., ni), the mean of the class I projection feature vector is, within the projection space, the nearest classification rule is: if the sample y meets: At the same time, the minimum distance classification rule is: If sample y meets Just compile it: Allsamples = []; Global Pathname; Global Y; Global X; Global P; Global Train_num; Global M; Global N; m = 112 ; % Rown = 92 ; % Columntrain_num =200 ; Gt = Zeros (n, n); pathname = ' C: \

-power method. Basically, I can follow this idea to write it down smoothly. I wrote it myselfCodePut it in the idempotence (this is one of the reasons why I later gave up using my own anti-idempotence ). The algorithm I wrote can also be used for exercises, and the matrix with smaller sizes cannot be seen, but it is unreliable to solve large-scale matrices, therefore, this is just a record of your work. Later, I found that the problem I solved was not to find the feature values of a general la

here:Step 2: Solving by matrix methodWe also see that the wiki finally says that solution with eigendecompositions is the eigenvalue decomposition.Here is a detailed explanation of how it is done.Turn 4 mds ppt (from your own class teacher's ppt):Explaining it is actually very simple:1) constructs a matrix T, and then finds that the T matrix can be calculated entirely from D.2) t this matrix can be decomposed ah, then the inside eigenvalue if greater than or equal to 0, you can open the square

Original: http://www.cnblogs.com/leonwen/p/5158947.html　　The algorithm is ported by MATLAB (see the previous blog post for details). But the final output is inconsistent with MATLAB, it is found that in the invocation of the internal function Eig to solve eigenvalues and eigenvectors, both eigenvalues are consistent, but the eigenvectors are different.But, theoretically, it makes sense, because eigenvectors are inherently non-unique. The most puzzling

follows:>>> A = np. ones (2, 2 ))>>> B = np. eye (2)>>> Print np. vstack (a, B ))[[1. 1.][1. 1.][1. 0.][0. 1.]>>> Print np. hstack (a, B ))[[1. 1. 1. 0.][1. 1. 0. 1.] Check whether the two functions involve the shortest copy problem:Copy codeThe Code is as follows:>>> C = np. hstack (a, B ))>>> Print c[[1. 1. 1. 0.][1. 1. 0. 1.]>>> A [1, 1] = 5>>> B [1, 1] = 5>>> Print c[[1. 1. 1. 0.][1. 1. 0. 1.]We can see that the change of elements in a and B does not affect c. Deep copy Array The array obje

matrix matrices, and the column represents the feature, where the percentage represents the variance ratio of the number of features required before taking the default to 0.9" "defPCA (datamat,percentage=0.9): #averaging for each column, because the mean value is subtracted from the calculation of the covarianceMeanvals=mean (datamat,axis=0) meanremoved=datamat-meanvals#CoV () Calculating varianceCovmat=cov (meanremoved,rowvar=0)#using the Eig ()

the inner area width of the first matched element (including padding, excluding borders).Here is an example:CSS code block style type="Text/css"> . Div{ width: px ; Height: + px ; background-color: Green ; padding: tenpx ; Border: px solid #009999 ; margin: px ;} style>jquery code block $(function(){ console.log($(‘div‘).width()+‘+‘+$(‘div‘).innerWidth()+‘+‘+$(‘div‘).outerWidth()); var k = $(‘div‘).height()+‘+‘+ $(‘div‘).innerHeight()+‘+‘+$(‘div‘).outerHeight()+

#define NSLOG (FORMAT, ...) fprintf (stderr, "%s\n", [[NSString Stringwithformat:format, # #__VA_ARGS__] utf8string]);#import int main (int argc, const char * argv[]) {@autoreleasepool {Variable groups inherit immutable groups1, create. Set the number of elements to createNsmutablearray *arr=[nsmutablearray Arraywithcapacity:7];2. Add an element to the arrayNsarray *[email protected][@ "Mon", @ "Tue", @ "Wed", @ "Thu", @ "Fri", @ "sat", @ "Sun"];//immutable variable groupNsmutablearray *arr2=[ns

#import int main (int argc, const char * argv[]) {@autoreleasepool {Create an array1. Quickly create an array @[]Nsarray *[email protected][@ "MON", @ "TUE", @ "WED", @ "THU", @ "FRI", @ "SAT", @ "SUN"];2. Create an empty arrayNsarray *arr=[[nsarray Alloc]init];Nsarray *arr1=[nsarray Array];Note end of array using nil (null) to finish cannot be deletedNsarray *arr2=[nsarray arraywithobjects:@ "Apple", @ "pear", @ "banana", nil];Nsarray *arr3=[nsarray arraywithobject:@ "B"];CopyNsarray *newarr=[n

#import int Main (int argc, const Char * argv[]) { @autoreleasepool { // variable array inheritance immutable variable group //1. Create A set number of elements to create nsmutablearray *mutarr=[nsmutablearray arraywithcapacity:7]; //2. add an element to an array nsarray *arr=@[@ "MON",@ "TUE",@ "WED",@ "THU",@ "FRI", @ "SAT",@ "SUN"]; nsmutablearray *mutarray=[nsmutablearray arraywitharray: arr]; [Mutarray addobject:@ "EIG