gnu-octave / gnu-octave/statistics
Difference in `iforest` results.
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Description
1
In MATLAB:
>> iforest ([])
ans =
IsolationForest
CategoricalPredictors: []
ContaminationFraction: 0
ScoreThreshold: NaN
NumLearners: 100
NumObservationsPerLearner: 0
Properties, Methods
In Octave:
octave:5> iforest ([]);
error: iforest: X must be a nonempty real numeric matrix.
error: called from
IsolationForest at line 102 column 9
iforest at line 77 column 3
2
In MATLAB:
>> iforest([1])
ans =
IsolationForest
CategoricalPredictors: []
ContaminationFraction: 0
ScoreThreshold: NaN
NumLearners: 100
NumObservationsPerLearner: 1
Properties, Methods
In Octave:
octave:6> iforest([1]);
error: iforest: NUMOBSERVATIONSPERLEARNER must be an integer in [3, N].
error: called from
IsolationForest at line 141 column 9
iforest at line 77 column 3
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
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- Open a pull request that references the issue number.
Research direction
Start with the iforest entry point and the IsolationForest validation paths reported at lines 77, 102, and 141. Compare handling of empty input and a single observation with MATLAB's behavior, then inspect existing tests for iforest if available. Done means these inputs no longer produce the reported Octave errors while preserving validation for genuinely invalid data.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- matlab
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Active
- Clarity
- Mostly clear
- Newbie friendliness
- 57/100