temp=x*theta'-y;sqrerrors=temp.^2;theta=theta-learning_rate*(1/m)*(temp'*x);Jcost(step)=(1/2*m)*sum(sqrerrors);disp(step),disp(Jcost(step))end figure;plot(Jcost)title('The relation between J and iteration ');ylabel('J')xlabel('iteration')legend('\alpha = 0.07')figureplot(...
Python has methods for finding a relationship between data-points and to draw a line of linear regression. We will show you how to use these methods instead of going through the mathematic formula.In the example below, the x-axis represents age, and the y-axis represents speed. We have ...
Machine Learning 学习笔记2 - linear regression with one variable(单变量线性回归) 一、Model representation(模型表示) 1.1 训练集 由训练样例(training example)组成的集合就是训练集(training set), 如下图所示, 其中(x,y)是一个训练样例,(x(i),y(i))是第i个训练样例. 1.2 假设函数 使用某种学习算法对...
SVD与主成分的关系:特征值越大,方差越大。 三、Robust regression鲁棒线性回归(Laplace/Student似然+均匀先验) 因为先验服从均匀分布,所以求鲁棒线性回归即求Laplace/Student最大似然。在heavy tail(奇异点较多)情况下用鲁棒线性回归,因为Laplace/Student分布比高斯分布更鲁棒。 似然函数为: 由于零点不可微,所以求解析解...
多项式回归基本概念对于线性回归,数据都是线性的,目标是寻找一条直线,尽可能的拟合样本。但实际任务中,数据往往是非线性,因此需对线性回归算法进行一些转换改造,即多项式回归。 多项式回归中,数据不太具有…
文章为博主学习Coursera上的Machine Learning课程的笔记,来记录自己的学习过程,欢迎大家一起学习交流 个人博客连接: JMX的个人博客 02:Linear Regression 仍然以房价预测作为示例,具体示例仍需见课程内容。 符号含义: m 为数据集的大小 x’s为输入数据 y’s为对应的目标输出结果 (x,y)为所有训练数据 (xi, yi)为...
A[Traning Set]-->B[Learning Algorithm] B-->h X[size of house]-->h h-->Y[Estimated price] 其中h:hyphothesis 意思并不够贴切 How do we representh? 5.cost function 接上文的linear regression问题,对于regression问题来说,这里的损失函数应当是一个优化问题: ...
{'linear regression','data','prediction'})2.正规方程法:1.x=load('ex2x.dat');2.y=load('ex2y.dat');3.m=length(x)4.x=[ones(m,1),x];5.theta=inv(x'*x)*x'*y6.figure7.plot(x(:,2),y,'o');8.%plot3(x(:,2),x*theta,'-g','Linewidth',2);9.p1=plot3(x(:,2),...
Well,regression is used basically when we are dealing with continuous sets of data and classification is applied when the data set used is scattered. To start with, we are going to discuss one of thesimplest regression i.e. linear regressionandwe will code a simple machine learning programme ...
(x,y)(x,y)(x,y) : one training example (x(i),y(i))(x^{(i)},y^{(i)} )(x(i),y...吴恩达《Machine Learning》-Linear Regression with Multiple Variables多元线性回归(四) 多特征情况Multiple Features 多特征角标解释: m 样本个数 n 特征个数 本例中,n=4 (x1,x2,x3,x4) x(i)...