Package org.apache.mahout.df.node

Examples of org.apache.mahout.df.node.Node.classify()

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    // predict the label for the out-of-bag elements
    if (callback != null) {
      log.debug("Oob error estimation");
      for (int index = 0; index < data.size(); index++) {
        if (sampled[index] == false) {
          int prediction = tree.classify(data.get(index));
          callback.prediction(treeId, index, prediction);
        }
      }
    }
   
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    for (int treeId = 0; treeId < trees.size(); treeId++) {
      Node tree = trees.get(treeId);
     
      for (int index = 0; index < data.size(); index++) {
        int prediction = tree.classify(data.get(index));
        callback.prediction(treeId, index, prediction);
      }
    }
  }
 
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    // predict the label for the out-of-bag elements
    if (callback != null) {
      log.debug("Oob error estimation");
      for (int index = 0; index < data.size(); index++) {
        if (!sampled[index]) {
          int prediction = tree.classify(data.get(index));
          callback.prediction(treeId, index, prediction);
        }
      }
    }
   
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    for (int treeId = 0; treeId < trees.size(); treeId++) {
      Node tree = trees.get(treeId);

      for (int index = 0; index < data.size(); index++) {
        int prediction = tree.classify(data.get(index));
        callback.prediction(treeId, index, prediction);
      }
    }
  }
 
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    // predict the label for the out-of-bag elements
    if (callback != null) {
      log.debug("Oob error estimation");
      for (int index = 0; index < data.size(); index++) {
        if (sampled[index] == false) {
          int prediction = tree.classify(data.get(index));
          callback.prediction(treeId, index, prediction);
        }
      }
    }
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    for (int treeId = 0; treeId < trees.size(); treeId++) {
      Node tree = trees.get(treeId);

      for (int index = 0; index < data.size(); index++) {
        int prediction = tree.classify(data.get(index));
        callback.prediction(treeId, index, prediction);
      }
    }
  }
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    for (int treeId = 0; treeId < trees.size(); treeId++) {
      Node tree = trees.get(treeId);

      for (int index = 0; index < data.size(); index++) {
        int prediction = tree.classify(data.get(index));
        callback.prediction(treeId, index, prediction);
      }
    }
  }
 
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