Machine Learning 5 Basic Operations

最新推荐文章于 2023-01-18 20:32:49 发布

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最新推荐文章于 2023-01-18 20:32:49 发布

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文章标签：机器学习

本文链接：https://blog.youkuaiyun.com/MONKEY3233/article/details/72763846

Machine Learning 5 Basic Operations

5-4 Plotting data

T = [0:0.1:1]
Y1 = sin(2*pi*4*t)
Plot(t,y1) //绘图程序
Hold on 在原图基础上绘制
Xlabel(‘time’)
Ylabel(‘value’)
Legend(‘sin’,’cos’) 为线进行标注
Title(‘my plot’) 标题
Print -dpng ‘myplot.png’ 保存
Close 关闭图像
Figure(1); plot(t,y1);
Figute(2);plot(t,y2);
Subplot(1,2,1); %Divides plot a 1x2 grid
Axis([0.5 1 -1 1])
Clf 干掉所有的图片
Imagesc(A) 可视化矩阵
Imagesc(A), colorbar, colormap gray; 为图片添加bar，设置颜色为灰色

5-5 Control Statements for, while, if statements

语法上不对缩进有要求

for i = 1:10,
    v(i) =  2^i;
    end;
indices = 1:10;
for i = indices.
    disp(i);
end;

while

while i <= 5,
    v(i) = 100;
    i = i+1;
end;

break

while true,
    v(i) = 999;
    i = i + 1;
    if(i == 6),
        break;
    end;
end;

if else

if v(1) == 1,
    disp('The value is one');
    elseif v(1) == 2,
        disp('The value is two');
    else
        disp('end');
end;

exit/quit 退出octave
function 使用时，要把函数放在当前空间

function y = squareThisNumber(x)
y = x^2;

function [y1, y2] = squareAndCubeThisNumber(x); % 返回多个值
y1 = x^2;
y2 = x^3;

function J = costFunctionJ(X, y, theta)
% X is the "design matrix" containing our training examples.
% y i the class labels
m = size(X, 1); % number of training examples
predictions = X*theta; % predictions of hypothesis on all m examples
sqrErrors = (predictions - y).^2; % squared errors

J = 1/(2*m) * sum(sqrErrors);