先来一个现实生活中的例子,这里的例子是房子尺寸和房价的模型关系表达。 通过学习Linear Regression可以进行预测某一size的房子prices是多少。 Regression问题属于Supervised Learning监督学习问题,预测连续值,Classification分类是预测离散值,上一个Introduction已经介绍过。 在上一张图的坐标点就是这里的训练集合。这里我们定...
要解决房价预测问题,我们实际上是要将训练集“喂”给我们的学习算法,进而学习得到一个假设h,然后将我们要预测的房屋的尺寸作为输入变量输入给h,预测出该房屋的交易价格作为输出变量输出为结果。那么,对于我们的房价预测问题,我们该如何表达h? 一种可能的表达是h(x)=ax+b,...
Linear regression on one variable
因为只有一个特征 所以是单变量线性回归问题 a b就是代价参数 求ab就是建模 ab算完和实际的差距叫建模误差 寻找ab平方和最小点 就是代价函数 也叫平方误差函数 这就是代价函数了 在两个参数下 真实值与求出的值的差的平方和 除以2m 其实就是求误差的平均数 而最接近真实值的两个参数 就是使这个表达式最...
linearregression函数输出拟合值 Linear Regression with One Variable model Representation 以上篇博文中的房价预测为例,从图中依次来看,m表示训练集的大小,此处即房价样本数量;x表示输入变量或feature(特征),此处即房子面积;y是输出变量或目标变量,此处即房子价格。(x,y)是训练集中的一个样本,如图中加上右上角(i)...
由图可知为监督学习,诺一种可能的表达方式为: h θ ( x ) = θ 0 + θ 1 x h_\theta \left( x \right)=\theta_{0} + \theta_{1}x hθ(x)=θ0+θ1x,因为只含有一个特征/输入变量,因此这样的问题叫作单变量线性回归(Linear Regression with One Variable)问题。 图为用单变量线性回归模型来...
Simple linear regression refers to the method of predicting the response with a single variable. It assumes that there is a certain relationship between the two.Mathematically, we assume that this relationship is y^=β^0+β^1x In the formula, the coefficients are unknown, we need to find th...
Simple linear regression It’s called simple for a reason: If you are testing a linear relationship between exactly two continuous variables (one predictor and one response variable), you’re looking for a simple linear regression model, also called a least squares regression line. Are you lookin...
Multiple linear regression (MLR) is a statistical technique that uses several explanatory variables to predict the outcome of a response variable.
In linear regression, every dependent value has a single corresponding independent variable that drives its value. For example, in the linear regression formula of y = 3x + 7, there is only one possible outcome of "y" if "x" is defined as 2. ...