func (self *nnServer) apiLearn(w http.ResponseWriter, r *http.Request) {
if !self.requireMethods(w, r, []string{"POST"}) {
return
}
session, err := self.getSession(w, r)
if err != nil {
return
}
var req ApiLearnRequest
decoder := json.NewDecoder(r.Body)
err = decoder.Decode(&req)
if err != nil {
self.errorResponse(w, http.StatusBadRequest, "request could not been decoded: "+err.Error())
}
conf := &perceptron.PerceptronConf{
Inputs: req.Inputs,
LearningRate: req.LearningRate,
Threshold: req.Threshold,
Iterations: req.Iterations,
}
net := perceptron.BuildPerceptronNet(conf)
netUuid, err := uuid.NewV4()
if err != nil {
self.log.Error(err.Error())
}
netId := netUuid.String()
self.nets[netId] = net
session.Values["netId"] = netId
err = session.Save(r, w)
if err != nil {
self.log.Error(err.Error())
}
weights, errors, err := net.Train(req.TrainData)
if err != nil {
self.log.Error(err.Error())
return
}
data := self.makeData()
data["weights"] = net.W
data["iterations"] = weights
data["iterations_errors"] = errors
resp := ApiResponse{
Status: "ok",
Data: data,
}
self.apiOkResponse(w, &resp)
}
func perceptron_test() {
trainSet := []util.TrainExample{
util.TrainExample{Input: []float64{1, 1, 1,
0, 0, 0,
0, 0, 0}, Output: []float64{0}},
util.TrainExample{Input: []float64{0, 0, 0,
1, 1, 1,
0, 0, 0}, Output: []float64{0}},
// util.TrainExample{Input:[]float64{0, 0, 0,
// 0, 0, 0,
// 1, 1, 1}, Output:[]float64{0}},
util.TrainExample{Input: []float64{1, 0, 0,
1, 0, 0,
1, 0, 0}, Output: []float64{1}},
util.TrainExample{Input: []float64{0, 1, 0,
0, 1, 0,
0, 1, 0}, Output: []float64{1}},
util.TrainExample{Input: []float64{0, 0, 1,
0, 0, 1,
0, 0, 1}, Output: []float64{1}},
}
conf := &perceptron.PerceptronConf{
Inputs: 9,
LearningRate: 1,
Iterations: 1000,
Threshold: 20,
}
net := perceptron.BuildPerceptronNet(conf)
weights, errors, _ := net.Train(trainSet)
fmt.Println(weights)
fmt.Println(errors)
for t := range trainSet {
prediction, _ := net.Predict(trainSet[t].Input)
fmt.Println(trainSet[t].Input, "=>", prediction)
}
}
