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package nn | |
import ( | |
"fmt" | |
"strings" | |
"github.com/go-gota/gota/dataframe" | |
"github.com/gofiber/fiber/v2" | |
) | |
type NN struct { | |
CSVData string `json:"csv_data"` | |
Features []string `json:"features"` | |
Target string `json:"target"` | |
Epochs int `json:"epochs"` | |
HiddenSize int `json:"hidden_size"` | |
LearningRate float64 `json:"learning_rate"` | |
ActivationFunc string `json:"activation"` | |
TestSize float64 `json:"test_size"` | |
Df *dataframe.DataFrame | |
XTrain dataframe.DataFrame | |
YTrain dataframe.DataFrame | |
XTest dataframe.DataFrame | |
YTest dataframe.DataFrame | |
} | |
func NewNN(c *fiber.Ctx) (*NN, error) { | |
newNN := new(NN) | |
err := c.BodyParser(newNN) | |
if err != nil { | |
return nil, fmt.Errorf("invalid JSON data: %v", err) | |
} | |
df := dataframe.ReadCSV(strings.NewReader(newNN.CSVData)) | |
newNN.Df = &df | |
return newNN, nil | |
} | |
func (nn *NN) Train() { | |
// train test split the data | |
// iterate n times where n = nn.Epochs | |
// use backprop algorithm on each iteration | |
// to fit the model to the data | |
} | |