Example #1
0
 List <double> Train(double x, double y, double r)
 {
     return(ann.Go(new List <double> {
         x, y
     }, new List <double> {
         r
     }));
 }
Example #2
0
    List <double> Train(double i1, double i2, double o)
    {
        List <double> inputs  = new List <double>();
        List <double> outputs = new List <double>();

        inputs.Add(i1);
        inputs.Add(i2);
        outputs.Add(o);
        return(ann.Go(inputs, outputs));
    }
Example #3
0
    private List <double> Train(int i1, int i2, int o)
    {
        List <double> inputs  = new List <double>();
        List <double> outputs = new List <double>();

        inputs.Add(i1);
        inputs.Add(i2);
        outputs.Add(o);
        return(model.Go(inputs, outputs));
    }
Example #4
0
    /// <summary>
    /// Set parameters for training
    /// </summary>
    /// <param name="input1"></param>
    /// <param name="input2"></param>
    /// <param name="output"></param>
    /// <returns></returns>
    List <double> Train(double input1, double input2, double output) //can change it for more inputs and outputs.
    //for example how to onload data from DB here and work with it and after that save it
    {
        List <double> inputs  = new List <double>();
        List <double> outputs = new List <double>();

        inputs.Add(input1);
        inputs.Add(input2);
        outputs.Add(output);
        return(ann.Go(inputs, outputs));
    }
Example #5
0
    // Use this for initialization
    void Start()
    {
        List <double> result = new List <double>();

        ann = new ANN(2, 1, 1, 2, 0.8f);
        for (int i = 0; i < 10000; i++)
        {
            sumSquareError = 0;
            result         = ann.Go(new List <double> {
                0, 0
            }, new List <double> {
                0
            });
            sumSquareError += Mathf.Pow((float)result[0] - 0, 2);

            result = ann.Go(new List <double> {
                0, 1
            }, new List <double> {
                1
            });
            sumSquareError += Mathf.Pow((float)result[0] - 1, 2);

            result = ann.Go(new List <double> {
                1, 0
            }, new List <double> {
                1
            });
            sumSquareError += Mathf.Pow((float)result[0] - 1, 2);

            result = ann.Go(new List <double> {
                1, 1
            }, new List <double> {
                0
            });
            sumSquareError += Mathf.Pow((float)result[0] - 0, 2);
        }
        Debug.Log("SSE: " + sumSquareError);
    }
    private List <double> Run(double bx, double by, double bvx, double bvy, double px, double py, double pv, bool train)
    {
        List <double> inputs  = new List <double>();
        List <double> outputs = new List <double>();

        inputs.Add(bx);
        inputs.Add(by);
        inputs.Add(bvx);
        inputs.Add(bvy);
        inputs.Add(px);
        inputs.Add(py);
        outputs.Add(pv);

        if (train)
        {
            return(ann.Train(inputs, outputs));
        }
        else
        {
            return(ann.Go(inputs, outputs));
        }
    }