使用支持向量回归分析竞价与曝光次数关系 - MATLAB代码示例

%20导入数据%0Adata%20%3D%20xlsread('Impression%26%26CPC.xlsx',%20'Sheet1');%0Abid%20%3D%20data(:,%202);%20%2F%2F%20竞价%0Aimpression%20%3D%20data(:,%201);%20%2F%2F%20曝光次数%0A%0A%2F%2F%20计算曝光次数的上下四分位数和IQR%0AQ1%20%3D%20prctile(impression,%2025);%0AQ3%20%3D%20prctile(impression,%2075);%0AIQR%20%3D%20Q3%20-%20Q1;%0A%0A%2F%2F%20定义异常值的阈值（例如，超过2倍IQR）%0Athreshold%20%3D%202%20*%20IQR;%0A%0A%2F%2F%20找到所有包含异常值的行索引%0Aoutlier_rows%20%3D%20impression%20%3C%20(Q1%20-%20threshold)%20%7C%20impression%20%3E%20(Q3%20+%20threshold);%0A%0A%2F%2F%20删除包含异常值的行%0Abid_cleaned%20%3D%20bid(~outlier_rows);%0Aimpression_cleaned%20%3D%20impression(~outlier_rows);%0A%0A%2F%2F%20支持向量回归拟合%0Aepsilon%20%3D%200.1;%20%2F%2F%20%CE%B5参数，控制拟合的容忍度%0Amodel%20%3D%20fitrlinear(bid_cleaned,%20impression_cleaned,%20'Epsilon',%20epsilon);%0A%0A%2F%2F%20预测拟合值%0Ay_fit%20%3D%20predict(model,%20bid_cleaned);%0A%0A%2F%2F%20数据可视化（删除异常值后）%0Ascatter(bid_cleaned,%20impression_cleaned);%0Ahold%20on;%0Aplot(bid_cleaned,%20y_fit,%20'r');%0Axlabel('竞价');%0Aylabel('曝光次数');%0Atitle('竞价与曝光次数关系（支持向量回归拟合）');%0Alegend('数据点',%20'拟合线');%0Ahold%20off;%0A%0A%2F%2F%20计算拟合曲线与实际数据之间的相关系数%0Acorrelation%20%3D%20corrcoef(impression_cleaned,%20y_fit);%0Ar%20%3D%20correlation(1,%202);%0A%0A%2F%2F%20输出相关系数%0Adisp(['相关系数：',%20num2str(r)]);%0A