最近刚开始接触机器学习,在这里使用c#模拟一元线性回归,先上图看效果
因为源码中有一些控件是自己封装的,所以就不上传可运行的程序集了,贴出核心代码,以供参考,如有不对,请多多给予建议
private void ryButtonX1_Click(object sender, EventArgs e) { string[] xnum = richTextBox1.Text.Trim().Split(',');//x值 string[] ynum = richTextBox2.Text.Trim().Split(',');//y值 if (xnum.Length != ynum.Length) { MessageBox.Show("输入数据有误!"); return; } ryTextBoxX1.Text = xnum.Length+"";//个数 decimal xsum = 0;//x值求和 decimal ysum = 0;//y值求和 for(int i = 0; i < xnum.Length; i++) { xsum = xsum + ConvertExtend.ToDecimal(xnum[i],0); ysum = ysum + ConvertExtend.ToDecimal(ynum[i], 0); } decimal xAve = ConvertExtend.ToDecimal(xsum / xnum.Length, 0);//x平均值 decimal yAve = ConvertExtend.ToDecimal(ysum / xnum.Length, 0);//y平均值 ryTextBoxX3.Text = string.Format("{0:N}", xAve);//保留两位小数 ryTextBoxX4.Text = string.Format("{0:N}", yAve); decimal molecule = 0;//分子 decimal Denominator = 0;//分母 for (int i = 0; i < xnum.Length; i++) { molecule = molecule + (ConvertExtend.ToDecimal(xnum[i], 0) - xAve) * (ConvertExtend.ToDecimal(ynum[i], 0) - yAve); Denominator = Denominator+(ConvertExtend.ToDecimal(xnum[i], 0) - xAve) * (ConvertExtend.ToDecimal(xnum[i], 0) - xAve); } ryTextBoxX2.Text = string.Format("{0:N}", molecule / Denominator);//斜率 ryTextBoxX5.Text = (yAve - (molecule / Denominator) * xAve)+"";//截距 if (ConvertExtend.ToDecimal(ryTextBoxX5.Text, 0) < 0) { ryTextBoxX6.Text = ryTextBoxX2.Text + "X" + ryTextBoxX5.Text; }else { ryTextBoxX6.Text = ryTextBoxX2.Text + "X+" + ryTextBoxX5.Text; } #region 画点 chartLabTrend.ChartAreas[0].AxisX.CustomLabels.Clear(); Listlx = new List (); List l1 = new List (); for (int i = 1; i <= xnum.Length; i++) { CustomLabel label1 = new CustomLabel(); if (xnum[i - 1] != "") { label1.Text = ConvertExtend.ToDecimal(xnum[i - 1],0).ToString(); label1.ToPosition = i * 2; chartLabTrend.ChartAreas[0].AxisX.CustomLabels.Add(label1); label1.GridTicks = GridTickTypes.Gridline; lx.Add(i); if (ynum[i - 1] == null) { l1.Add(null); } else { l1.Add(ConvertExtend.ToDecimal(ynum[i - 1],0)); } } } chartLabTrend.Series[0].Points.DataBindXY(lx, l1); #endregion #region 画线 chartLabTrend.ChartAreas[0].AxisX.CustomLabels.Clear(); List lx1 = new List (); List l11 = new List (); for (int i = 1; i <= xnum.Length; i++) { CustomLabel label2 = new CustomLabel(); if (xnum[i - 1] != "") { label2.Text = ConvertExtend.ToDecimal(xnum[i - 1], 0).ToString(); label2.ToPosition = i * 2; chartLabTrend.ChartAreas[0].AxisX.CustomLabels.Add(label2); label2.GridTicks = GridTickTypes.Gridline; lx1.Add(i); if (ynum[i - 1] == null) { l11.Add(null); } else { l11.Add(ConvertExtend.ToDecimal(ConvertExtend.ToDecimal(xnum[i - 1],0)*molecule / Denominator + ConvertExtend.ToDecimal(ryTextBoxX5.Text,0), 0)); } } } chartLabTrend.Series[1].Points.DataBindXY(lx1, l11); #endregion }
以上就是c# 模拟线性回归的示例的详细内容,更多关于c# 模拟线性回归的资料请关注其它相关文章!