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mirror of https://github.com/sjwhitworth/golearn.git synced 2025-05-11 19:29:47 +08:00

37 Commits

Author SHA1 Message Date
Yaser Azfar
ae8d7f7baa adds error checking for err variable that were being left unchecked 2019-12-27 12:10:38 +13:00
frozenkp
6b3f7ddab2 format 2018-06-16 22:11:59 +08:00
Richard Townsend
2428dfa7de Fix various other little errors 2018-03-24 00:20:45 +00:00
Richard Townsend
e7fee0a2d1 Reformat, fix tests 2017-09-10 21:10:54 +01:00
Richard Townsend
fc110aab48 Fix bad import, reformat 2017-09-10 20:35:34 +01:00
Richard Townsend
e27215052b ensemble: tests pass 2017-09-10 19:30:02 +01:00
Richard Townsend
3e80230d3d meta: passes the tests, seems to be flaky 2017-09-10 18:24:40 +01:00
Richard Townsend
c18d50d217 meta: tests passing 2017-09-10 17:43:17 +01:00
Richard Townsend
768d2cd19f meta: tests are almost passing 2017-09-10 16:59:05 +01:00
Richard Townsend
ead76bdd7e I think I'm going to refocus this whole thing 2017-09-09 12:31:32 +01:00
Anzel Lai
481da97eca Fix go vet complaints 2016-06-14 00:56:47 +01:00
Richard Townsend
8fe06e7332 Support for individual class weightings 2014-10-30 23:28:26 +00:00
Richard Townsend
981d43f1dd Adds support for multi-class linear SVMs.
This patch
  * Adds a one-vs-all meta classifier into meta/
  * Adds a LinearSVC (essentially the same as LogisticRegression
    but with different libsvm parameters) to linear_models/
  * Adds a MultiLinearSVC into ensemble/ for predicting
    CategoricalAttribute  classes with the LinearSVC
  * Adds a new example dataset based on classifying article headlines.

The example dataset is drawn from WikiNews, and consists of an average,
min and max Word2Vec representation of article headlines from three
categories. The Word2Vec model was computed offline using gensim.
2014-10-05 11:15:41 +01:00
Amit Kumar Gupta
9f67f73330 Convert some tests to goconvey, and improve assertions along the way 2014-08-22 13:39:29 +00:00
Amit Kumar Gupta
1809a8b358 RandomForest returns error when fitting data with fewer features than the RandomForest plans to use
- BaseClassifier Predict and Fit methods return errors
- go fmt ./...

Conflicts:
	ensemble/randomforest.go
	ensemble/randomforest_test.go
	trees/tree_test.go
2014-08-22 13:39:29 +00:00
Amit Kumar Gupta
529b3bcaa5 Avoid renaming packages on import 2014-08-22 13:39:29 +00:00
Amit Kumar Gupta
947ee8380e Return error instead of panicking when unable to get confusion matrix 2014-08-22 13:39:29 +00:00
Amit Kumar Gupta
14aad31821 Consistently use (t *testing.T) instead of T or testEnv 2014-08-22 08:44:41 +00:00
Amit Kumar Gupta
695aec6eb6 Favor idiomatic t.Fatalf over panic for test failures 2014-08-22 08:07:55 +00:00
Amit Kumar Gupta
45545d6ebd Remove Println's from automated test suite since they aren't assertions 2014-08-22 07:58:01 +00:00
Amit Kumar Gupta
21bb2fc9fa Remove redundant import renames 2014-08-22 07:21:24 +00:00
Amit Kumar Gupta
94e5843bcf go fmt ./... 2014-08-22 06:55:20 +00:00
Richard Townsend
47341b2869 base: Cleaned up duplicate Attribute resolution functions 2014-08-03 15:17:20 +01:00
Richard Townsend
3b3b23a221 meta: merge from v2-instances 2014-08-03 15:17:11 +01:00
Niclas Jern
627a5537d3 Comments should be of the form "<Struct> ..." or "<MethodName> ..." 2014-07-18 13:48:28 +03:00
Niclas Jern
daac7a278d Omit unused second value from range statements. 2014-07-18 13:17:19 +03:00
Remo Hertig
f77c1dcde0 use multiple return values instead of an array in InstancesTrainTestSplit 2014-06-06 21:33:17 +02:00
Richard Townsend
4fd88d834f @mish15's re-write of Predict() 2014-05-23 12:19:10 +01:00
Richard Townsend
ce2afe34fb Benchmarking 2014-05-23 12:16:11 +01:00
Richard Townsend
7a33d2b9b2 Making Fit() more idiomatic 2014-05-20 09:06:59 +01:00
Richard Townsend
61f65e04aa Merge branch 'randomforests-upstream' of github.com:Sentimentron/golearn into randomforests-upstream 2014-05-19 12:59:25 +01:00
Richard Townsend
a6072ac9de Package documentation 2014-05-19 12:59:11 +01:00
Richard Townsend
ab39d0c972 Fixed race conditions 2014-05-18 20:59:46 +01:00
Richard Townsend
45ca6063f1 Not sure if this bagging version is better or not
More more similar to "Attribute bagging:improving accuracy of classifier ensembles by using random feature subsets" (Brill)
2014-05-18 11:49:35 +01:00
Richard Townsend
c516907b13 Passes all the tests 2014-05-17 17:35:10 +01:00
Richard Townsend
cf165695c8 ChiMerge seems to improve accuracy 2014-05-17 16:20:56 +01:00
Richard Townsend
fdb67a4355 Initial work on decision trees
Random Forest has occasional disastrous accuracy:
	 never seen that happen in WEKA
2014-05-14 14:00:22 +01:00