以某个名为 house style 的分类特征为例,该特征拥有一组离散的可能值(共三个),即 Tudor, ranch, colonial。通过将 house style 表示成分类数据,相应模型可以学习 Tudor、ranch 和 colonial 分别对...
The code in the following snippet demonstrates the simplest ML.NET application. This example constructs a linear regression model to predict house prices using house size and price data.C# コピー using Microsoft.ML; using Microsoft.ML.Data; class Program { public record HouseData { public ...
The code in the following snippet demonstrates the simplest ML.NET application. This example constructs a linear regression model to predict house prices using house size and price data. C#Copy usingMicrosoft.ML;usingMicrosoft.ML.Data;classProgram{publicrecordHouseData {publicfloatSize {get;set; }pu...
The code in the following snippet demonstrates the simplest ML.NET application. This example constructs a linear regression model to predict house prices using house size and price data. C#复制 usingMicrosoft.ML;usingMicrosoft.ML.Data;classProgram{publicrecordHouseData {publicfloatSize {get;set; }pu...
(xixi,yiyi) =ithithtraining example (第i个训练样本) h = hypothesis (假设) 单变量性线回归: hθ(x)=θ0+θ1xhθ(x)=θ0+θ1x st=>start: Training Set op=>operation: Learning Algorithm op1=>end: hypothesis(假设) x=>inputoutput: sizeof house ...
1单变量线性回归Linear Regression with One Variable 1.1模型表达Model Representation 一个实际问题,我们可以对其进行数据建模。在机器学习中模型函数一般称为hypothsis。这里假设h为: 我们从简单的单变量线性回归模型开始学习。 1.2代价函数Cost Function 代价函数也有很多种,下面的是平方误差Squared error function: ...
In the following example, we’ll use the size of the house. Linear regression models the relationship between the Y "Label" and the X "Feature", in this case the relationship between the house price and size, with the equation: Y = intercept + (coefficient * X) + error. The coefficien...
Machine learning: ML uses a variety of algorithms, including linear regression, decision trees, support vector machines, etc. These algorithms often have simpler structures. Deep learning: Neural networks are the core of deep learning. The interconnected “neurons” in multiple layers give them immens...
The code in the following snippet demonstrates the simplest ML.NET application. This example constructs a linear regression model to predict house prices using house size and price data. C#複製 usingMicrosoft.ML;usingMicrosoft.ML.Data;classProgram{publicrecordHouseData {publicfloatSize {get;set; }pu...
Regression: The model is trained to predict a continuous value instead of a discrete class. Examples: house price prediction, stock price forecasting, and demand forecasting. Learn more about supervised learning: Supervised Learning – Towards Data Science ...