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- package main
- import (
- "fmt"
- "log"
- "os"
- neuralnetwork "./neuralnetworkbase"
- teach "./teach"
- )
- func main() {
- sizes := []int{13, 14, 14, 3}
- nn, _ := neuralnetwork.NewNeuralNetwork(sizes, 0.1, 100)
-
-
-
-
-
-
-
-
- teacher := teach.NewTextDataReader("./wine.data")
- nn.Teach(teacher)
-
-
-
-
-
-
-
-
- outFile, err := os.OpenFile("./data", os.O_CREATE|os.O_TRUNC|os.O_WRONLY, 0666)
- if err != nil {
- log.Fatal(err)
- }
- defer outFile.Close()
- nn.SaveState(outFile)
- outFile.Close()
- failCount := 0
- teacher.Reset()
- for teacher.NextData() {
- dataSet, expect := teacher.GetData()
- index, _ := nn.Predict(dataSet)
- if expect.At(index, 0) != 1.0 {
- failCount++
- fmt.Printf("Fail: %v, %v\n\n", teacher.Index(), expect.At(index, 0))
- }
- }
- fmt.Printf("Fail count: %v\n\n", failCount)
- nn = &neuralnetwork.NeuralNetwork{}
- inFile, err := os.Open("./data")
- if err != nil {
- log.Fatal(err)
- }
- defer inFile.Close()
- nn.LoadState(inFile)
- inFile.Close()
- failCount = 0
- teacher.Reset()
- for teacher.NextData() {
- dataSet, expect := teacher.GetData()
- index, _ := nn.Predict(dataSet)
- if expect.At(index, 0) != 1.0 {
- failCount++
- fmt.Printf("Fail: %v, %v\n\n", teacher.Index(), expect.At(index, 0))
- }
- }
- fmt.Printf("Fail count: %v\n\n", failCount)
- }
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