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Implement the simple Binary Relevance kNN (both version) as per: http://link.springer.com/chapter/10.1007%2F978-3-540-87881-0_40
Preferably subclass the meta.BR classifier.
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Hello,
I posted this question in the Google groups but it does not seem to attract any attention. So I am posting this here. If this is not correct, please tell me.
I have taken some Scikit sourc…
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**Step 1) Tried to change the training image in example.py**
```
ocr.train( ImageFile('otherimagefile') )
```
**Step 2) Bumped into an error**
```
Exception: The provided file is not grounded
```
…
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For the sake of tweaking the ranking algorithm used by kNN classifier it'd be good to be able to specify the `Similarity` to use (at construction time) in the underlying `IndexSearcher`.
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Migrat…
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The help says that if a `.f` is not supplied, then a built-in one will be used. Currently that doesn't happen, for example:
``` r
library(MLPUGS)
x
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Allow to define MLT _minDocFreq_ and _minTermFreq_ for _KNearestNeighborClassifier_ to tweak recall of _MoreLikeThis_ queries.
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Migrated from [LUCENE-5348](https://issues.apache.org/jira/browse/…
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> k-means can be used for supervised learning too. I will use both clustering algo, and evaluate using the measures such as precision, recall and f-measure. Should probably use the classifier with a h…
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1. Determine multilabel classifiers implemented in Orange.
2. Figure out the data structure needed for using Orange.
3. Test out one of the classifiers.
tsalo updated
8 years ago
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Right now we're generating a lot of data that gets stored across many small files. This data situation is quickly going to become a mess, so we should get more organized by having our data collection …
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Should just be a matter of looking up each classifier for its inputs and the typical ranges used.
tsalo updated
8 years ago