(objective function)或代价函数(cost function). 最小化目标函数的可行解x∗(也就是对所有可行x, 都有c′x∗≤c′x) 被称为最优可行解 (optimal feasible solution), 或者最优解 (optimal solution).c′x∗的值被称作最优值 (optimal cost). 另一方面, 若对于所有始数K, 我们都能找到一可行解x,...
我们定义了cost function(损失函数): 如果你以前学过线性回归,你可能认为这个函数和最小均方损失函数(least-squares cost function )很类似,并提出普通最小二乘法回归模型(ordinary least squares regression model)。 三、普通最小二乘法(ordinary least squares) 最小二乘法(又称最小平方法)是一种数学优化技术,...
当(y^{(i)} - h_\theta(x^{(i)}))已经很小时,说明已经达到拟合的要求,\theta的值就不变了。 We’d derived the LMS rule for when there was only a single training example. There are two ways to modify this method for a training set of more than one example: 批处理梯度下降 随机梯度下...
当已经很小时,说明已经达到拟合的要求,的值就不变了。 We’d derived the LMS rule for when there was only a single training example. There are two ways to modify this method for a training set of more than one example: 批处理梯度下...
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训练集的数据进行训练, 我们可以得到假设函数(Hypothesis Function), 如下图所示. 在房价的例子中,假设函数就是一个房价关于房子面积...
If I want to estimate the cost of an office building, things like floor space, number of building entrances, age of building and the number of offices would all be part of the equation. Let’s see an example.Typing the LINEST formula into cell G29 and executing it, we get:...
It is also important to examine the properties of a linear function. But first, why even study linear functions? Here is a real-world example to show its usefulness. Consider a bake sale committee that earns $150.00 a month in cost while incurring a one-time start-up cost of $200.00. ...
It is also important to examine the properties of a linear function. But first, why even study linear functions? Here is a real-world example to show its usefulness. Consider a bake sale committee that earns $150.00 a month in cost while incurring a one-time start-up cost of $200.00. ...
%X-training example,y-实际数值,alpha-learning rate2function [theta, J_history] = gradientDescent(X, y, theta, alpha, num_iters)34% theta =GRADIENTDESENT(X, y, theta, alpha, num_iters) updates theta by5%taking num_iters gradient steps with learning rate alpha67%Initialize some useful value...
functionJ=computeCost(X,y,theta)%Initialize some useful values m=length(y);%numberoftraining examples%===YOURCODEHERE===%Instructions:Compute the costofa particular choiceoftheta%You shouldsetJto the cost.J=sum((X*theta-y).^2)/(2*m);%===end gradientDescent.m 代码语言:javascript 复制 ...