Regression is performed on continuous data, while classification is performed on discrete data. Regression can be anything from predicting someone's age, the house of a price, or value of any variable. Classification includes predicting whatclasssomething belongs to (such as whether a tumor is beni...
python machine-learning linear-regression-models xgboost-algorithm Updated Feb 15, 2025 Jupyter Notebook s1dewalker / Model_Validation Star 0 Code Issues Pull requests Model Management in Python. Steps involved in Model Validation and tuning. Testing Model Assumptions in Factor Analysis with OLS...
J_history=np.zeros((num_iters,1))foriterinrange(num_iters):# 对J求导,得到 alpha/m*(WX-Y)*x(i),(3,m)*(m,1)X(m,3)*(3,1)=(m,1)theta=theta-(alpha/m)*(X.T.dot(X.dot(theta)-y))J_history[iter]=computeCost(X,y,theta)returnJ_history,theta iterations=10000#迭代次数 alph...
MachineLearning_Python/LinearRegression/LinearRegression.py/ Jump to cclaussModernize Python 2 code to get ready for Python 3 Latest commit202ff3bon Jan 4, 2018History 1contributor 116 lines (86 sloc)3.76 KB RawBlame #-*- coding: utf-8 -*- ...
机器学习(三)---多变量线性回归(Linear Regression with Multiple Variables) 同样是预测房价问题 如果有多个特征值 那么这种情况下 假设h表示为 公式可以简化为 两个矩阵相乘 其实就是所有参数和变量相乘再相加 所以矩阵的乘法才会是那样 那么他的代价函数就是 同样是寻找...
Tensorflow是目前非常流行的deeplearning框架,学习Tensorflow最好的方法是github上的tf项目https://github.com/tensorflow/tensorflow 或者阅读极客学院主导翻译的中文教程http://wiki.jikexueyuan.com/project/tensorflow-zh/how_tos/reading_data.html。 此处对tensorflow的基本语法不予赘述,直接贴上源码: ...
The script shown in the steps below is main.py — which resides in the GitHub repository and is forked from the “Dive Into Deep learning” example repository. You can find code samples within the pytorch directory. For our regression example, you’ll need the following: Python 3 PyTorch ...
通过看其他人在kaggle上分享的notebook以及自己的一些理解,记录一下Linear Regression的学习过程,也算是完成作业中的report.pdf。 二、Linear Regression(预测PM2.5) 1、准备工作 (1)作业要求(如图一所示) 图一 (2)train.csv、test.csv 链接:https://pan.baidu.com/s/1ZeOASD7SdyMUYwjo0uDaqA ...
吴恩达机器学习(十三)—— ex5:Regularized Linear Regression and Bias v.s. Variance(MATLAB+Python),一、线性回归的正则化1.1可视化数据集1.2正则化线性回归的代价函数1.3线性回归梯度的正则化1.4拟合线性回归二、偏差和方差2.1学习曲线三、多项式回归3.1学习多项
(1)首先我们的目的是要用regression来代替classification(为啥要替代?因为PLA/Pocket是NP-hard的问题,不好整;而Linear Model在最优化之后,求解比较容易了),如果regression和classification在性能上差不多,那就可以替代了。 (2)因此,我们把cross-entropy error来scale成0/1 error的upper bound,目的就是让cross-entropy...