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
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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(); List< decimal ?> lx = new List< decimal ?>(); List< decimal ?> l1 = new List< decimal ?>(); 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< decimal ?> lx1 = new List< decimal ?>(); List< decimal ?> l11 = new List< decimal ?>(); 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服务器之家其它相关文章!
原文链接:https://www.cnblogs.com/cui0614/p/11293793.html