本文整理汇总了C#中INode.Calculate方法的典型用法代码示例。如果您正苦于以下问题：C# INode.Calculate方法的具体用法？C# INode.Calculate怎么用？C# INode.Calculate使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类INode的用法示例。
在下文中一共展示了INode.Calculate方法的6个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C#代码示例。
示例1: CalculateFitness
public double CalculateFitness(INode individual)
{
// Keep track the average error
double totalError = 0;
const int numberTests = 50;
for (int i = 0; i < numberTests; ++i)
{
int input1 = RandomUtil.Random.Next(100);
int input2 = RandomUtil.Random.Next(100);
int input3 = RandomUtil.Random.Next(100);
int input4 = RandomUtil.Random.Next(100);
if (input4 == 0) input4 = 1;
double expectedResult = (double)input1 + (double)input2*(double)input3/(double)input4;
double error = expectedResult - individual.Calculate(new List<double>{input1, input2, input3, input4}, new List<List<double>>());
error = Math.Abs(error);
error = Math.Abs(Math.Sqrt(0.1*error));
totalError += error;
// Add some error if the error is too large taking account of the size
//if (error > 0.3) totalError += individual.GetNodes().Count/100.0;
}
return totalError/numberTests;
}示例2: SimplifyNode
private static void SimplifyNode(ref INode result)
{
// Check for an InputVariableNode in result
if (result.GetNodes().Any(n => n.GetType() == typeof(InputVariableNode) || n.GetType() == typeof(InputSizeNode)
|| n.GetType() == typeof(CollectionSizeNode) || n.GetType() == typeof(SumNode)))
return;
// We don't have an InputVariableNode, so we can simplify into a single constant
double constant = result.Calculate(new List<double>(), new List<List<double>>());
result = new ConstantNode(result.Context, constant);
}示例3: CalculateFitness
public double CalculateFitness(INode individual)
{
// Keep track the average error
double totalError = 0;
const int numberTests = 50;
for (int i = 0; i < numberTests; ++i)
{
int input = RandomUtil.Random.Next(100);
double expectedResult = input*20.0;
double error = expectedResult - individual.Calculate(new List<double>{input}, new List<List<double>>());
error = Math.Abs(error);
totalError += Math.Abs(Math.Sqrt(0.1*error));
}
return totalError/numberTests;
}示例4: CalculateFitness
public double CalculateFitness(INode individual)
{
// Don't allow nodes to get too big
if (individual.GetNodes().Count > 30) return 1000;
if (this.perfectNode == null) this.CreatePerfectNode();
// Keep track the average error
double totalError = 0;
const int numberTests = 50;
for (int i = 0; i < numberTests; ++i)
{
int top = RandomUtil.Random.Next(1000);
int size = RandomUtil.Random.Next(10);
if (size == 0) size = 1;
double expectedTotal = 0.0;
List<double> input = new List<double>();
for (int j = 0; j < size; ++j)
{
double expectedItem = RandomUtil.Random.Next(top);
input.Add(expectedItem);
expectedTotal += expectedItem;
}
double expectedResult = expectedTotal/(double) size;
List<List<double>> inputs = new List<List<double>>();
inputs.Add(input);
double error = expectedResult - individual.Calculate(new List<double>(), inputs);
error = Math.Abs(error);
error = Math.Abs(Math.Sqrt(0.1*error));
totalError += error;
// Add some error if the error is too large taking account of the size
//if (error > 0.3) totalError += individual.GetNodes().Count/100.0;
}
return totalError/(double)(numberTests);
}示例5: CalculateFitness
public double CalculateFitness(INode individual)
{
// Don't allow nodes to get too big
if (individual.GetNodes().Count > 30) return 1000;
// We don't allow an individual to take more than 1 second to test
DateTime startTime = DateTime.Now;
// Keep track the average error
double totalError = 0;
// Keep track of results to make sure that we have some non-zero
bool haveNonZero = false;
//INode ideal = MakeVarianceNode();
foreach (TestCase testCase in this.testCases)
{
double calculate = individual.Calculate(new List<double>(), testCase.Inputs);
if (calculate != 0) haveNonZero = true;
double error = testCase.ExpectedResult - calculate;
//error = Math.Abs(Math.Sqrt(0.1*error));
if (testCase.ExpectedResult != 0) error = error/testCase.ExpectedResult;
totalError += Math.Abs(error);
// Add some error if the error is too large taking account of the size
//if (error > 0.3) totalError += individual.GetNodes().Count/100.0;
// If we've gone over a second, stop with a high error
if ((DateTime.Now - startTime).TotalMilliseconds > StandardDeviationFitnessFunction.maximumRunLength)
return Double.MaxValue;
}
if (!haveNonZero) return Double.MaxValue;
return totalError/(double)(this.testCases.Count);
}示例6: Train
public double Train(INode Node, int Epochs = 1000)
{
if (Epochs < 1)
throw new ArgumentException("At least 1 epoch is required.");
if (DataSets.Length < 1)
throw new ArgumentException("No DataSets have been loaded.");
if (InputCount != Node.Inputs)
throw new ArgumentException("The given INode does not have the same number of Inputs as the DataSets.");
if (OutputCount != 1)
throw new ArgumentException("An INode only supports 1 output.");
for (int i = 0; i < Epochs; i++)
{
foreach (var dataSet in DataSets)
{
double delta = 0;
double result = Node.Calculate(dataSet.Inputs, dataSet.Outputs.First(), ref delta);
// weight delta = learning rate * error * weight
AdjustNode(Node, dataSet.Inputs, LearningRate * delta);
}
}
double SSE = 0;
foreach (var dataSet in DataSets)
{
double result = Node.Calculate(dataSet.Inputs);
SSE += Math.Pow(dataSet.Outputs.First() - result, 2);
}
return SSE;
}