514c4f3384
Use four categories instead of all in doc. class. example
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Accidentally set to all in the course of fixing TfidfTransformer.
2011-07-04 15:30:45 +02:00
09d33353e0
Merge pull request #228 from larsmans/tfidf
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TfidfTransformer: user-selectable norm
2011-07-04 05:15:41 -07:00
48a3cd1d4c
Better performance of Ax=b solver when b is 2d and A is sparse, and add
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new tol parameter.
2011-07-01 16:56:07 +09:00
d673f828aa
document classification example doesn't demo only linear classifiers anymore
2011-06-29 13:59:05 +02:00
1cd62ba2ad
Use 10 neighbors in k-NN document classification
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Boosts F1 from 0.435 to 0.531.
Still a very bad score, while Manning, Raghavan and Schuetze
(Introduction to Information Retrieval) report much higher scores
for similar tasks, with a euclidean distance metric. TODO: find
out why our scores are so low.
2011-06-26 15:35:06 +02:00
1ff5944260
Adapt kNN classifier to sparse input
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Includes demo on document classification task (with poor performance,
but very acceptable speed).
2011-06-22 11:57:49 +02:00
7880af76c9
Optimize BernoulliNB + improve docstring + add to doc-class example
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Still two orders of magnitude slower than MultinomialNB because of loop in
_joint_log_likelihood.
2011-06-06 11:37:41 +02:00
d7499b864a
fix message in document classification example
2011-06-06 10:55:32 +02:00
bd8c8febb7
reformulate MultinomialNB as linear classifier
2011-05-23 22:31:15 +02:00
3dd1d00532
naive bayes name change MNNB->MultinomialNB
2011-05-11 19:20:43 +03:00
595bf835c2
Merge remote branch 'upstream/master'
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Conflicts:
scikits/learn/naive_bayes.py
2011-05-11 17:27:37 +03:00
6ee9d68250
rename rng to random_state
2011-05-04 09:45:16 +02:00
5c6a4530a9
Added sparse MNNB and modified the textual examples to benchmark it.
2011-04-11 21:40:11 +03:00
ee416469ff
FIX: update the examples to match the new text feature extraction API
2011-04-03 03:58:09 +02:00
637c70038c
renamed load_* to fetch_* when network connection is potentially involved
2011-03-19 18:39:45 +01:00
27acf9100d
Merge branch 'master' into 20newsgroups-dataset
2011-03-03 18:50:58 +01:00
21175e3629
MISC: Fix example to adjust to eps -> tol
2011-03-02 06:52:58 +01:00
6c4ecf3fb8
cosmit
2011-02-27 16:08:13 +01:00
123c0f8c11
better name: rename class_names to target_names for consistency
2011-02-27 12:15:50 +01:00
a7a6431627
cosmit
2011-02-27 02:19:14 +01:00
7e65409bf2
cosmit
2011-02-27 02:10:26 +01:00
323a423553
first stab at factoring the 20 newsgroups dataset loading
2011-02-27 02:05:02 +01:00
8ee253a0af
Fix 20newsgroup example.
2011-01-20 23:25:34 +09:00
95817f8495
Add RidgeClassifier to 20newsgroup classification example.
2011-01-19 00:13:54 +09:00
46a2d551a3
fixed imports in non-auto examples.
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COSMIT import paths in plot examples.
Rephrased SGD outline in linear_model.rst
2010-12-03 10:28:08 +01:00
fe662553ea
finalized sgd module renaming.
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renamed ClassifierSGD to SGDClassifier (same for Regressor)
updated setup.py files
updated examples
updated docs
2010-11-30 12:14:30 +01:00
eda509886d
changed loss function names in SGD (squaredloss -> squared_loss; also for modified_huber).
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Fixed examples after SGD class renaming.
COSMIT in sgd documentation.
2010-11-25 11:03:10 +01:00
44352e8e8c
factorize out shuffling dataset since it might be useful by default
2010-11-13 20:23:04 +01:00
337f25f9f9
cosmit
2010-11-13 17:48:02 +01:00
f061783636
Include models with L1 and Elastic-Net penalty.
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Optional arguments for printing the classification report and confusion matrix.
2010-11-13 17:26:01 +01:00
0492a5c67e
Cosmit
2010-11-12 07:35:00 +01:00
a21319d942
move the mlcomp SGD example as a generic 20 newsgroup classification example
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with sparse features
2010-11-12 05:05:45 +01:00
Lars Buitinck