stanfordnlp/CoreNLP · error · Exception

Number of thresholds and number of labels do not match.

Error message

Number of thresholds and number of labels do not match.

What it means

A guard IllegalArgumentException thrown when caller-supplied thresholds array length differs from the number of labels in the labelIndex while loading weights into a LinearClassifier; thresholds are indexed per label, so a mismatch means the weights/threshold array was built for a different label set.

Solutions

1. Provide one threshold per label (thresholds.length == labelIndex.size())
2. Rebuild the thresholds array from the label index
3. Pass a null/empty thresholds if defaults are desired where supported

When it happens

Trigger: Thrown at src/edu/stanford/nlp/classify/LinearClassifier.java:1255 when the library encounters an invalid state.

Common situations: See trigger scenarios.

AI-assisted analysis of stanfordnlp/CoreNLP@1b7edd19c4 (2026-09-10). Data as JSON: /api/errors/8b2d26ac53026379. Report an issue: GitHub.

Appendix: source

Thrown at src/edu/stanford/nlp/classify/LinearClassifier.java:1255

   *  @param featureIndex An index from F to integers used to index the features in the weights array
   *  @param labelIndex An index from L to integers used to index the labels in the weights array
   */
  public LinearClassifier(double[][] weights, Index<F> featureIndex, Index<L> labelIndex) {
    this.featureIndex = featureIndex;
    this.labelIndex = labelIndex;
    this.weights = weights;
    thresholds = new double[labelIndex.size()];
    // Arrays.fill(thresholds, 0.0); // not needed; Java arrays zero initialized
  }

  // todo: This is unused and seems broken (ignores passed in thresholds)
  public LinearClassifier(double[][] weights, Index<F> featureIndex, Index<L> labelIndex,
      double[] thresholds) throws Exception {
    this.featureIndex = featureIndex;
    this.labelIndex = labelIndex;
    this.weights = weights;
    if (thresholds.length != labelIndex.size())
      throw new Exception("Number of thresholds and number of labels do not match.");
    thresholds = new double[thresholds.length];
    int curr = 0;
    for (double tval : thresholds) {
      thresholds[curr++] = tval;
    }
    Arrays.fill(thresholds, 0.0);
  }

  private static <F, L> Counter<Pair<F, L>> makeWeightCounter(double[] weights, Index<Pair<F, L>> weightIndex) {
    Counter<Pair<F,L>> weightCounter = new ClassicCounter<>();
    for (int i = 0; i < weightIndex.size(); i++) {
      if (weights[i] == 0) {
        continue; // no need to save 0 weights
      }
      weightCounter.setCount(weightIndex.get(i), weights[i]);
    }
    return weightCounter;
  }

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