func MultiClassRun(classifier algo.MultiClassClassifier, train_path string, test_path string, pred_path string, params map[string]string) (float64, 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, err } test_dataset := core.NewDataSet() err = test_dataset.Load(test_path, global) if err != nil { return 0.5, err } classifier.Init(params) accuracy := MultiClassRunOnDataSet(classifier, train_dataset, test_dataset, pred_path, params) return accuracy, nil }
func MultiClassTest(classifier algo.MultiClassClassifier, test_path string, pred_path string, params map[string]string) (float64, 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 } test_dataset := core.NewDataSet() err := test_dataset.Load(test_path, global) if err != nil { return 0.0, err } accuracy := MultiClassRunOnDataSet(classifier, nil, test_dataset, pred_path, params) return accuracy, nil }
func MultiClassTrain(classifier algo.MultiClassClassifier, 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 }