Beispiel #1
0
func AlgorithmRun(classifier algo.Classifier, train_path string, test_path string, pred_path string, params map[string]string) (float64, []*eval.LabelPrediction, error) {
	global, _ := strconv.ParseInt(params["global"], 10, 64)
	train_dataset := core.NewDataSet()

	err := train_dataset.Load(train_path, global)

	if err != nil {
		return 0.5, nil, err
	}

	test_dataset := core.NewDataSet()
	err = test_dataset.Load(test_path, global)
	if err != nil {
		return 0.5, nil, err
	}
	classifier.Init(params)
	auc, predictions := AlgorithmRunOnDataSet(classifier, train_dataset, test_dataset, pred_path, params)

	return auc, predictions, nil
}
Beispiel #2
0
func AlgorithmTest(classifier algo.Classifier, test_path string, pred_path string, params map[string]string) (float64, []*eval.LabelPrediction, error) {
	global, _ := strconv.ParseInt(params["global"], 10, 64)

	model_path, _ := params["model"]
	classifier.Init(params)
	if model_path != "" {
		classifier.LoadModel(model_path)
	} else {
		return 0.0, nil, nil
	}

	test_dataset := core.NewDataSet()
	err := test_dataset.Load(test_path, global)
	if err != nil {
		return 0.0, nil, err
	}

	auc, predictions := AlgorithmRunOnDataSet(classifier, nil, test_dataset, pred_path, params)

	return auc, predictions, nil
}
Beispiel #3
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
}