// Copyright 2016 Huawei Technologies Co. Ltd.
//
// Licensed to the Apache Software Foundation (ASF) under one or more
// contributor license agreements.  See the NOTICE file distributed with
// this work for additional information regarding copyright ownership.
// The ASF licenses this file to You under the Apache License, Version 2.0
// (the "License"); you may not use this file except in compliance with
// the License.  You may obtain a copy of the License at
//
//   http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

package model;

import java.util.ArrayList;

import weka.core.Instances;

import predictor.*;


public interface ModelInterface {
	public String getDatapath();
	public ArrayList<PredictorInterface> getPredictors();
	
	public void loadTrainingData(String path);
	public void loadRawLog(String path);
	public Instances getTrainingInstances();
	public void setPreprocessedInstances(Instances instances);
	public Instances getPreprocessedInstances();
	public void savePreprocessedInstances(String path);
	public void addPredictor(String shortName);
	public void crossValidatePredictors(int numFold);
	public void crossValidatePredictors(int numFold, long seed);
	public void selectTrainingMethod();
	public void trainPredictors() throws Exception;
	public void benchmark(int rounds, String filename) throws Exception;

	public String getPredictorNames();
	public String toString();
	public void saveSettings(String filename) throws Exception;
	public void saveResults(String filename) throws Exception;
}