// 分类运算 private void classifyButton_Click(object sender, EventArgs e) { //前提检验 if (SelectedPCXHelper.GetSelPCXFromLB().Count == 0 || SelectedPCXHelper.GetUnselPCXList().Count == 0) { MessageBox.Show(this, "您还未提取样本特征,或者还未设置测试样本集!", "提示信息", MessageBoxButtons.OK); } else { string correctRate = null; //正确率 string myfilepath = filepathText.Text.ToString(); Features feature; #region 这里做一个文件名为unknown.pcx的判断 string filename = FeatureHelper.GetUnknownName(myfilepath); if (filename.ToLower().Equals("unknown")) { feature = new Features(myfilepath); } else { int classID = Convert.ToInt32(FeatureHelper.GetUpperFoldername(myfilepath)); feature = new Features(myfilepath, classID); } #endregion #region Bayes分类法 if (rbBayes.Checked) { #region 数据初始化 CheckInit(); double correctCount = 0.0; #endregion IList sampleList = FeatureHelper.GetFeaturesList(); //获取原始训练样本 //从降维器获取降维后的新样本 IList newSampleList = MDAHelper.GetMDSampleList(); MVHelper.SetSampleList((ArrayList)newSampleList); Bayes bayes = Bayes.GetInstance(); bayes.TrainSampleList = newSampleList; //向贝叶斯分类器注入降维后的训练样本 //int classID = Convert.ToInt32(FeatureHelper.GetUpperFoldername(myfilepath)); //Features feature = new Features(myfilepath, classID); feature = MDAHelper.MDSample(feature); //测试样本降维 int testClassID = bayes.DecisionFunction(feature); //用贝叶斯决策进行测试样本分类 //结果显示 lblunknownclassify.Text = testClassID.ToString("000"); if (feature.classID == testClassID) { lblerrorinfo.Text = "Bayes分类法分类正确"; lblerrorinfo.ForeColor = Color.Green; } //unknown.pcx处理 else if (feature.classID == -1) { } else { lblerrorinfo.Text = "Bayes分类法分类失败"; lblerrorinfo.ForeColor = Color.Green; } } #endregion #region Kn近邻法 if (rbKn.Checked) { #region 相关数据初始化 CheckInit(); int testResult = -1; double correctCount = 0.0; int kvalue = Constant.kvalue; #endregion #region 效的情况下进行计算 if (KCheck(kvalue)) { KnNear my_knearest = new KnNear(); //int classID = Convert.ToInt32(FeatureHelper.GetUpperFoldername(myfilepath)); //Features currfeature = new Features(myfilepath, classID); testResult = my_knearest.DoK_nearest(feature, FeatureHelper.GetFeaturesList(), kvalue); //testResult为K近邻的分类结果 // 其实testResult的结果直接就是result求的值 string result = testResult.ToString("000"); lblunknownclassify.Text = result; result = ResultConvert(result); int testID = Convert.ToInt32(result); if (testID > 0 && testID == feature.classID) { //correctRate = "分类正确率: " + Constant.kn_Rate; lblerrorinfo.Text = "Kn近邻法分类正确"; lblerrorinfo.ForeColor = Color.Green; } //unknown.pcx处理 else if (feature.classID == -1) { } else { lblerrorinfo.Text = "Kn近邻法分类失败!"; lblerrorinfo.ForeColor = Color.Green; } } #endregion } #endregion #region 最近邻法 if (rbnearest.Checked) { #region 初始化 CheckInit(); int testResult = -1; double correctCount = 0.0; #endregion #region 最近邻分类 if (NearestCheck()) { Nearest nearest = new Nearest(); //int classID = Convert.ToInt32(FeatureHelper.GetUpperFoldername(myfilepath)); //Features currfeature = new Features(myfilepath, classID); testResult = nearest.Do_Nearest(feature, FeatureHelper.GetFeaturesList()); string result = testResult.ToString("000"); lblunknownclassify.Text = result; if (testResult > 0 && testResult == feature.classID) { lblerrorinfo.Text = "最近邻法分类正确"; lblerrorinfo.ForeColor = Color.Green; } //unknown.pcx处理 else if (feature.classID == -1) { } else { lblerrorinfo.Text = "最近邻法分类失败!"; lblerrorinfo.ForeColor = Color.Green; } } #endregion } #endregion } }
// 获取Dataset数据 public DataSet GetViewDS(out double ccount, out double crate, out int count) { #region 数据初始化 double correctCount = 0; double correctRate = 0.0; int testResult = 0; Nearest nearest = new Nearest(); IList testSampleList = FeatureHelper.GetTestFeaturesList(); //获取原始测试 #endregion #region DataGridView操作 dgv_result.DataSource = null; dgv_result.Rows.Clear(); dgv_result.Refresh(); DataSet ds = new DataSet(); DataTable dt = new DataTable(); dt.Columns.Add("样本路径", typeof(string)); dt.Columns.Add("样本类", typeof(string)); dt.Columns.Add("样本测试结果类", typeof(string)); dt.Columns.Add("正误判断", typeof(string)); foreach (Features feature in testSampleList) { testResult = nearest.Do_Nearest(feature, FeatureHelper.GetFeaturesList()); if (testResult > 0) { DataRow row = dt.NewRow(); string rightOrWrong = "×"; row[0] = feature.Filepath; row[1] = feature.classID; row[2] = string.Format("类{0}", testResult); //检查结果是否正确 if (testResult == feature.classID) { correctCount++; row[3] = " "; } else { row[3] = rightOrWrong; //this.knDataGridView.DefaultCellStyle.ForeColor = Color.Red; } dt.Rows.Add(row); } } ds.Tables.Add(dt); //this.dgv_result.DataSource = ds.Tables[0]; //SetControlPropertyValue(dgv_result, "DataSource", ds.Tables[0]); #endregion #region Kn近邻法性能显示 //correctRate = (correctCount / Convert.ToDouble(testSampleList.Count)) * 100.0; //Constant.kn_Rate = correctRate.ToString("0.000") + "%"; //lbl_result.Text = "测试样本总数 " + testSampleList.Count + " ,Kn近邻法判断正确 " // + correctCount + " 个,正确率为:" + Constant.kn_Rate; #endregion ccount = correctCount; crate = correctRate; count = testSampleList.Count; return(ds); }