public static NeuralNetwork Child(NeuralNetwork mum, NeuralNetwork dad)
{
NeuralNetwork child = new NeuralNetwork(mum);
for (int i = 0; i < child.Length; i++)
{
for (int j = 0; j < child[i].Length; j++)
{
for (int k = 0; k < child[i][j].Length; k++)
{
float value = child[i][j][k].x;
int rand = RandomF.Next(2);
if (rand == 0)
{
value = dad[i][j][k].x;
}
child[i][j][k].x = value;
}
}
if (!child[i].IsBiasNull())
{
for (int k = 0; k < child[i].GetBias().Length; k++)
{
float value = child[i].GetBias()[k].x;
int rand = RandomF.Next(2);
if (rand == 0)
{
value = dad[i].GetBias()[k].x;
}
child[i].GetBias()[k].x = value;
}
}
}
return(child);
}
private void formUI_Load(object sender, EventArgs e)
{
ToolTip toolTip = new ToolTip();
months.Add("January");
months.Add("February");
months.Add("March");
months.Add("April");
months.Add("May");
months.Add("June");
months.Add("July");
months.Add("August");
months.Add("September");
months.Add("October");
months.Add("November");
months.Add("December");
string path = @"images\";
string[] lines = File.ReadAllLines(path + "data.txt");
linesList.AddRange(lines);
for (int i = 0; i < lines.Length; i++)
{
string[] split = lines[i].Split(' ');
string name = split[0];
PictureBox pictureBoxPoster = new PictureBox()
{
Name = Path.GetFileName(name),
Location = new Point((int)Map.Float(0f,
RandomF.NextFloat(this.Width),
this.Width,
this.Width * padding,
this.Width - (this.Width * padding) - size.Width),
RandomF.Next(this.Height - size.Height)),
Image = Image.FromFile(path + name),
Size = size,
SizeMode = PictureBoxSizeMode.StretchImage,
Tag = i.ToString(),
BorderStyle = BorderStyle.FixedSingle
};
pictureBoxPoster.MouseDown += PictureBoxPoster_MouseDown;
pictureBoxPoster.MouseUp += PictureBoxPoster_MouseUp;
pictureBoxPoster.MouseMove += PictureBoxPoster_MouseMove;
toolTip.SetToolTip(pictureBoxPoster, split[0]);
pictureBoxes.Add(pictureBoxPoster);
this.Controls.Add(pictureBoxPoster);
// Categories
string[] categoriesArr = split[4].Split(',');
for (int j = 0; j < categoriesArr.Length; j++)
{
if (!categories.Contains(categoriesArr[j]))
{
categories.Add(categoriesArr[j]);
}
}
// Directors
string[] directorsArr = split[5].Split(',');
for (int j = 0; j < directorsArr.Length; j++)
{
if (!directors.Contains(directorsArr[j]))
{
directors.Add(directorsArr[j]);
}
}
// Stars
string[] starsArr = split[6].Split(',');
for (int j = 0; j < starsArr.Length; j++)
{
if (!stars.Contains(starsArr[j]))
{
stars.Add(starsArr[j]);
}
}
}
neuralNetwork = new NeuralNetwork(31 + 12 + 1 + categories.Count + directors.Count + stars.Count, 64, 1)
{
max_circle = 10000,
learning_rate = 0.5f,
momentum_rate = 0.96f
};
}
