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// 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;
}
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