roc curve matlab

Software Environment: MATLAB2013AI. Polynomial-fittingPolynomial fitting is the best fitting of the observed data by polynomial, which makes the error squared and the smallest at the observed data points.In Matlab, polynomial fitting is performed using function Ployfit and ployval.The function ployfit a polynomial representation of a smooth curve based on the observed data and the user-specified polynomial

Curve Fitting A data set on a known discrete point, known as a function value on a point set, constructs an analytic function (a graph of a curve) so as to be as close to a given value as possible at the original discrete point, a process known as curve fitting. The most commonly used curve fitting method is the least

make y ' =1/y; X ' =exp (-t) strong curves into linear models Y ' =a+b*x ' Matlab code to analyze and fit the calculation: Code one: (intentionally in this way when the data is low, enter data directly into the code) Clear CLC % Read population data (1971-2000) y=[33815 33981 34004 34165 34212 34327 34344 34458 34498 34476 34483 34488 34513 34497 34511 34520 34507 34509 34521 34513 34515 34517 34519 34519 34521 34521 34523 34525 34525 34527] % Rea

Curve Fitting in MATLAB In Matlab, The polyfit function can be used for fitting curves. This method is called polynomial fitting: Polynomial fitting: X = 0: 0.; y = [-0.447 1.978 3.28 6.16 7.08 7.34 7.66 9.56 9.48 9.30]; A = polyfit (X, Y, 2 ); % use quadratic polynomial curves to fit z = polyval (A, x); plot (X, Y, 'r * ', X, Z,' B '); Note: (X, y) In A = po

This line can be used to traverse all pixels in the image, but this is not done here, but only generates such a curve. In the program, H and W are the height and width of the final image, and N is the order of the Hilbert curve. Here, if n is equal to log2 (h) or log2 (W), the image will be completely white, and it will just traverse all pixels. Of course, if n is large, the image is completely white. Howev

matlab Two-dimensional curve drawing common methods, to keep the use of Grammar Plot (Y)Plot (X1,y1,...)Plot (X1,y1,linespec,...)Plot (..., ' PropertyName ', PropertyValue,...)Plot (Axes_handle,...)h = Plot (...)Hlines = Plot (' V6 ',...) Description Plot (y) if Y is an array of MXN, 1:m is x-axis, each column element in Y is y-coordinate, and n-curves are plotted, and if y is a vector of nx1 or 1xn, the y

1. Call Polyfit to have matlab calculate the coefficients of the polynomial that fits the data.y = mx + b, which requires m and B values, we can use a Matlab function called Polyfit (x, y, N), where n is the number of times we want Matlab to find the polynomial, for y = mx + b equation, we set n equal to 1, So the statement that is called will be Polyfit (x, Y, 1

1. The first is to extract the training log file;2. Then the MATLAB code:clear all; close all; Clc;log_file='/home/wangxiao/downloads/43_attribute_baseline.log'; FID= fopen (Log_file,'R'); Fid_accuracy= fopen ('/home/wangxiao/downloads/output_accuracy.txt','W'); Fid_loss= fopen ('/home/wangxiao/downloads/output_loss.txt','W'); Iteration={};loss={};accuracy={};p ath='/home/wangxiao/downloads/'; Fid_= fopen ([path,'Loss_file_.txt'],'a'); while(~feof (FI

As shown in the following figure, for the Hants Harmonic analysis of the single pixels of the vegetation growth season curve, now using a one-element six-time polynomial to fit the curve, and to solve the phenological parameters (beginning and end), in MATLAB programming implementation: Code: Year0=zeros (38998,1); For i=1:1:38998 if M (i,:) ==0

Please refer to the sourceProgram: Clear, CLC; format longx = (0: 0. 0:100) '; y_0 = besselj (0, x); % Y_1 = besselj (1, x); % level 1. Here, only order 0% y_2 = besselj (2, x); % second-order plot (x, y_0); grid on; axis ([0,100,-]); Title ('0-order besell Function Curve '); xlabel ('variable x'); ylabel ('variable y'); % draw envelope hold on; [Up, down] = envelope (x, y_0, 'spline '); plot (x, up, 'R'); plot (x, down, 'R '); The envelope is a s