public static TrainingSets GenerateDataSet1() { var dataset = new TrainingSets(); dataset.XList.Add(ParseDoubles(@" 0,0,0,1,1,0,0,0 0,0,1,0,0,1,0,0 0,1,0,0,0,0,1,0 1,0,0,0,0,0,0,1 1,0,0,0,0,0,0,1 0,1,0,0,0,0,1,0 0,0,1,0,0,1,0,0 0,0,0,1,1,0,0,0 ")); dataset.XList.Add(ParseDoubles(@" 0,0,0,1,1,0,0,0 0,0,0,1,1,0,0,0 0,0,0,1,1,0,0,0 0,0,0,1,1,0,0,0 0,0,0,1,1,0,0,0 0,0,0,1,1,0,0,0 0,0,0,1,1,0,0,0 0,0,0,1,1,0,0,0 ")); dataset.XList.Add(ParseDoubles(@" 0,0,1,1,1,0,0,0 0,1,0,0,0,1,0,0 0,0,0,0,0,0,1,0 0,0,0,0,0,1,0,0 0,0,0,0,1,0,0,0 0,0,0,1,0,0,0,0 0,0,1,0,0,0,0,0 0,1,1,1,1,1,1,1 ")); dataset.YList.Add(ParseDoubles("0,0,1")); //代表0 dataset.YList.Add(ParseDoubles("0,1,0")); //代表1 dataset.YList.Add(ParseDoubles("1,0,0")); //代表2 return(dataset); }
internal static TrainingSets GenerateDataSet3() { var dataset = new TrainingSets(); dataset.XList.Add(ParseDoubles("1,1,1,1,1,0,0,0,0")); dataset.XList.Add(ParseDoubles("0.9,1,1,1,1,0,0,0,0")); dataset.XList.Add(ParseDoubles("1,1,0.9,1,1,0,0,0,0")); dataset.XList.Add(ParseDoubles("1,1,1,1,1,1,0,0,0")); dataset.XList.Add(ParseDoubles("1,1,1,1,1,1,1,0,0")); dataset.XList.Add(ParseDoubles("1,1,1,0,1,0,0,0,0")); dataset.XList.Add(ParseDoubles("1,1,1,0,1,1,1,1,0")); dataset.XList.Add(ParseDoubles("1,1,1,0,1,1,1,1,0")); dataset.XList.Add(ParseDoubles("1,1,1,0,1,0,1,1,0")); dataset.XList.Add(ParseDoubles("0,0,0,0,0,1,1,1,1")); dataset.XList.Add(ParseDoubles("0,0,0,0,0,1,1.1,1,1")); dataset.XList.Add(ParseDoubles("0,0,0,0,0,1,1,1,1.1")); return(dataset); }
internal static TrainingSets GenerateDataSet2() { /* * 人口数,GDP,人均工资 */ var dataset = new TrainingSets(); { //SH var xs = new List <double>(); xs.Add(1000000); xs.Add(3000000); dataset.XList.Add(xs); } { //BJ var xs = new List <double>(); xs.Add(1500000); xs.Add(2500000); dataset.XList.Add(xs); } { //SZ var xs = new List <double>(); xs.Add(2000000); xs.Add(3000000); dataset.XList.Add(xs); } { //YC var xs = new List <double>(); xs.Add(50); xs.Add(20); dataset.XList.Add(xs); } return(dataset); }
public static TrainingSets GenerateDataSet1_2() { var dataset = new TrainingSets(); for (var i = 0; i < 100; i++) { List <double> bits = ParseInt2Doubles(i); dataset.XList.Add(bits); if (i % 2 == 0) { dataset.YList.Add(ParseDoubles("0"));//代表奇数 } else { dataset.YList.Add(ParseDoubles("1"));//代表奇数 } } return(dataset); }