matlab(8) Regularized logistic regression : 不同的λ(0,1,10,100)值对regularization的影响，对应不同的decision boundary\ 预测新的值和计算模型的精度predict.m

【matlab(8) Regularized logistic regression : 不同的λ(0,1,10,100)值对regularization的影响，对应不同的decision boundary\ 预测新的值和计算模型的精度predict.m】的更多相关文章

matlab(8) Regularized logistic regression : 不同的λ(0,1,10,100)值对regularization的影响，对应不同的decision boundary\ 预测新的值和计算模型的精度predict.m

不同的λ(0,1,10,100)值对regularization的影响\ 预测新的值和计算模型的精度 %% ============= Part 2: Regularization and Accuracies =============% Optional Exercise:% In this part, you will get to try different values of lambda and % see how regularization affects the decisio…

matlab(7) Regularized logistic regression : mapFeature(将feature增多) and costFunctionReg

Regularized logistic regression : mapFeature(将feature增多) and costFunctionReg ex2_reg.m文件中的部分内容 %% =========== Part 1: Regularized Logistic Regression ============% In this part, you are given a dataset with data points that are not% linearly separabl…

matlab(6) Regularized logistic regression : plot data(画样本图)

Regularized logistic regression : plot data(画样本图) ex2data2.txt 0.051267,0.69956,1-0.092742,0.68494,1-0.21371,0.69225,1-0.375,0.50219,1-0.51325,0.46564,1-0.52477,0.2098,1-0.39804,0.034357,1-0.30588,-0.19225,10.016705,-0.40424,10.13191,-0.51389,10.385…

machine learning(15) --Regularization:Regularized logistic regression

Regularization:Regularized logistic regression without regularization 当features很多时会出现overfitting现象,图上的cost function是没有使用regularization时的costfunction的计算公式 with regularization 当使用了regularization后,使θ1到n不那么大(因为要使J(θ)最小,θ12+θ22.....θn2->0这时θj要趋向于0),这样可以避免…

matlab(5) : 求得θ值后用模型来预测 / 计算模型的精度

求得θ值后用模型来预测 / 计算模型的精度 ex2.m部分程序 %% ============== Part 4: Predict and Accuracies ==============% After learning the parameters, you'll like to use it to predict the outcomes% on unseen data. In this part, you will use the logistic regression model%…

ResourceWarning: unclosed <socket.socket fd=864, family=AddressFamily.AF_INET, type=SocketKind.SOCK_STREAM, proto=0, laddr=('10.100.x.x', 37321), raddr=('10.1.x.x', 8500)>解决办法

将代码封装,并使用unittest调用时,返回如下警告: C:\python3.6\lib\collections\__init__.py:431: ResourceWarning: unclosed <socket.socket fd=864, family=AddressFamily.AF_INET, type=SocketKind.SOCK_STREAM, proto=0, laddr=('10.100.x.x', 37321), raddr=('10.1.x.x', 8500)> 解决…

Regularized logistic regression

要解决的问题是,给出了具有2个特征的一堆训练数据集,从该数据的分布可以看出它们并不是非常线性可分的,因此很有必要用更高阶的特征来模拟.例如本程序中个就用到了特征值的6次方来求解. Data To begin, load the files 'ex5Logx.dat' and ex5Logy.dat' into your program. This dataset represents the training set of a logistic regression problem with t…