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// Copyright 2010-2012, Google Inc.
// All rights reserved.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
//     * Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//     * Redistributions in binary form must reproduce the above
// copyright notice, this list of conditions and the following disclaimer
// in the documentation and/or other materials provided with the
// distribution.
//     * Neither the name of Google Inc. nor the names of its
// contributors may be used to endorse or promote products derived from
// this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
// "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
// LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
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// SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
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#ifndef MOZC_BASE_SVM_H_
#define MOZC_BASE_SVM_H_

#include <vector>
#include <utility>

// Simple linear SVM module:
// Original code stems from
// Zinnia: Online hand recognition system with machine learning,
// Modifed some for mozc purpose.

namespace mozc {
class SVM {
 public:
  // Perform SVM training.
  static bool Train(const vector<double> &y,  // label
                    const vector<vector<pair<int, double> > > &x,
                    double C,       // toralence parameter
                    vector<double> *w);  // output vector
 private:
  SVM() {}
  ~SVM() {}
};
}  // namespace mozc
#endif  // MOZC_BASE_SVM_H_