plot(testError[1,],ylim=range,type='l',col=rainbow(10)[1],xlab='degree',ylab='the estimated test MSE') for(seed in 2:10)points(testError[seed,],type='l',col=rainbow(10)[seed]) 每种颜色代表一次全体样本的随机对半划分 ### ##
plt.plot(k_range, k_scores) plt.xlabel('Value of K for KNN') plt.ylabel('Cross-Validated Accuracy') plt.show()发布于 2020-10-22 21:57 k 折交叉验证 机器学习 机器学习算法 赞同32添加评论 分享喜欢收藏申请转载 ...
步骤6：绘制ROC曲线 plot(lr_roc, col = "blue", main = "ROC Curve", xlab = "False Positive...
% evaluate the prediction error of model 2 X2 =Xtrain; hb2 = (X2'*X2)\(X2'*Ytrain); PE2(k) = (Ytest-Xtest*hb2)^2; end PE = [PE1 PE2]; boxplot(PE) mean(PE)©2022 Baidu |由 百度智能云 提供计算服务 | 使用百度前必读 | 文库协议 | 网站地图 | 百度营销...
plt.plot(k_range, k_score) plt.xlabel('Value of K for KNN') plt.ylabel('Cross-Validated MSE') plt.show() 一般来说准确率(accuracy)会用于判断分类(Classification)模型的好坏。 scores= cross_val_score(knn, X, y, cv=10, scoring='accuracy') ...
Plot the cross-validated sum of squared distances for each number of clusters. Get plot(cvdist) xlabel('Number of Clusters') ylabel('CV Sum of Squared Distances') In general, when determining how many clusters to use, consider the greatest number of clusters that corresponds to a significant...
plot_error <-function(x, y, sd, len = 1, col = "black"){ len<-len*0.05 arrows(x0 =x, y0 =y, x1 =x, y1 =y- sd,col=col, angle =90, length =len) arrows(x0 =x, y0 =y, x1 =x, y1 =y+ sd,col=col, angle =90, length =len) ...
plot /overlay 概念 变量间的关系有两种类型:确定性的函数关系和相关关系. 回归分析方法是处理变量间相关关系的统计分析工具. 回归分析用于确定一个变量(因变量)与另一些变量(自变量)间的相互依赖关系。回归分析是研究一个(或几个)因变量Y与另一些变量的相互依赖关系.具体地说,研究问题如下: ...
PE1(k)=(Ytest-Xtest*[hb1;0])^2;%[hb1;0]:beta0、beta1;beta2=0 %evaluatethepredictionerrorofmodel2 X2=Xtrain; hb2=(X2'*X2)\(X2'*Ytrain); PE2(k)=(Ytest-Xtest*hb2)^2; end PE=[PE1PE2]; boxplot(PE) mean(PE)...
Lift Chart (Analysis Services - Data Mining) Profit Chart (Analysis Services - Data Mining) Scatter Plot (Analysis Services - Data Mining) Describes steps for creating various accuracy charts. Testing and Validation Tasks and How-tos (Data Mining)See...