Example #1
0
func AlgorithmRunOnDataSet(classifier algo.Classifier, train_dataset, test_dataset *core.DataSet, pred_path string, params map[string]string) (float64, []*eval.LabelPrediction) {

	if train_dataset != nil {
		classifier.Train(train_dataset)
	}

	predictions := []*eval.LabelPrediction{}
	var pred_file *os.File
	if pred_path != "" {
		pred_file, _ = os.Create(pred_path)
	}
	for _, sample := range test_dataset.Samples {
		prediction := classifier.Predict(sample)
		if pred_file != nil {
			pred_file.WriteString(strconv.FormatFloat(prediction, 'g', 5, 64) + "\n")
		}
		predictions = append(predictions, &(eval.LabelPrediction{Label: sample.Label, Prediction: prediction}))
	}
	if pred_path != "" {
		defer pred_file.Close()
	}

	auc := eval.AUC(predictions)
	return auc, predictions
}
Example #2
0
func AlgorithmTrain(classifier algo.Classifier, train_path string, params map[string]string) error {
	global, _ := strconv.ParseInt(params["global"], 10, 64)
	train_dataset := core.NewDataSet()

	err := train_dataset.Load(train_path, global)

	if err != nil {
		return err
	}

	classifier.Init(params)
	classifier.Train(train_dataset)

	model_path, _ := params["model"]

	if model_path != "" {
		classifier.SaveModel(model_path)
	}

	return nil
}