MatrixXd predictions= input_X *theta; ArrayXd sqrErrors= (predictions -_y).array().square();doubleJ =1.0/ (2* rows) *sqrErrors.sum();returnJ; }classGradient_descent {public: Gradient_descent(MatrixXd&x, MatrixXd &y, MatrixXd &t,doubler=0.1,intm=3000): input_X(x), _y(y), the...
#感性调整 # W = W - learning_rate * gradient_E_w #理性调整 gradient_E_w = np.mean(2 * (Y_hat - Y) * X) gradient_E_b = np.mean(2 * (Y_hat -Y)) #训练函数 W = W - learning_rate * gradient_E_w B = B - learning_rate * gradient_E_b #最终的参数结果 print(f'Fina...
Linear regression using gradient descent function [final_theta, Js] = gradientDescent(X, Y, init_theta, learning_rate=0.01, max_times=1000) convergence = 0; m = size(X, 1); tmp_theta = init_theta; Js = zeros(m, 1); for i=1:max_times, tmp = learning_rate / m * ((X * ...
李宏毅老师机器学习课程笔记——Gradient descent 梯度下降 在上一篇笔记regression回归中,提到了回归过程中参数求解利用了梯度下降法,本篇笔记将对梯度下降法展开深入讨论。 梯度下降是机器学习过程中常见的优化算法,用于求解机器学习算法的模型参数。 一、理论 机器学习算法求解最优参数可以表示为: 其中,L(θ)为loss fu...
图解机器学习:如何用gradient descent一步一步求解最优linear regression 模型以及其他值得注意的细节.mp4 吴恩达机器学习课程笔记(图解版)_哔哩哔哩 (゜-゜)つロ 干杯~-bilibili p10
In this post you discovered the simple linear regression model and how to train it using stochastic gradient descent. You work through the application of the update rule for gradient descent. You also learned how to make predictions with a learned linear regression model. Do you have any que...
线性回归、梯度下降(Linear Regression、Gradient Descent) 实例 首先举个例子,假设我们有一个二手房交易记录的数据集,已知房屋面积、卧室数量和房屋的交易价格,如下表: 假如有一个房子要卖,我们希望通过上表中的数据估算这个房子的价格。这个问题就是典型的回归问题,这边文章主要讲回归中的线性回归问题。
all right, the model is linear regression. to find the parametersθ0,θ1,θ2of hypothesisprice=θ0+θ1x1+θ2x2 initialize the vectorθ=[θ0,θ1,θ2] minimize the error:error=0.5m∗∑mi=1(price(xi)−yi))2 to achieve the minimization we use the gradient descent algorithm due to...
Using ten-year car sales data, this research proposes a machine learning approach using gradient descent (GD) to fitting multiple linear regression for Thailand car sales forecasts. The resulted forecasting accuracy is then compared with that of a normal equation method (NE) as well as that ...
Invalid JSONThis GUI was designed to aid college professors to teach how linear regression with gradient descent works in practice. *GUI features; This GUI enables the user to generate scattered points randomly with linear behavior and use the gradient descent algorithm to fit iteratively a line ...