David Monllaó
de50490154
Neural networks partial training and persistency ( #91 )
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* Neural networks partial training and persistency
* cs fixes
* Add partialTrain to nn docs
* Test for invalid partial training classes provided
2017-05-23 09:03:05 +02:00
David Monllaó
4af8449b1c
Neural networks improvements ( #89 )
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* MultilayerPerceptron interface changes
- Signature closer to other algorithms
- New predict method
- Remove desired error
- Move maxIterations to constructor
* MLP tests for multiple hidden layers and multi-class
* Update all MLP-related tests
* coding style fixes
* Backpropagation included in multilayer-perceptron
2017-05-18 00:07:14 +02:00
David Monllaó
c0463ae087
Fix wrong docs references ( #79 )
2017-04-13 21:34:55 +02:00
Bill Nunney
8be19567a2
Update imputation example to use transform method ( #57 )
2017-03-09 20:41:15 +01:00
David Monllaó
8f122fde90
Persistence class to save and restore models ( #37 )
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* Models manager with save/restore capabilities
* Refactoring dataset exceptions
* Persistency layer docs
* New tests for serializable estimators
* ModelManager static methods to instance methods
2017-02-02 09:03:09 +01:00
David Monllaó
c1b1a5d6ac
Support for multiple training datasets ( #38 )
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* Multiple training data sets allowed
* Tests with multiple training data sets
* Updating docs according to #38
Documenting all models which predictions will be based on all
training data provided.
Some models already supported multiple training data sets.
2017-02-01 19:06:38 +01:00
Robert Boloc
aace5ff022
Fix documentation links
2017-01-05 20:37:48 +00:00
Ken Seah
8a0a9f09e2
Update array-dataset.md
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Method has already changed name to getTargets() instead of getLabels()
2016-11-04 00:03:49 +11:00
Patrick Florek
90038befa9
Apply comments / coding styles
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* Remove user-specific gitignore
* Add return type hints
* Avoid global namespace in docs
* Rename rules -> getRules
* Split up rule generation
Todo:
* Move set theory out to math
* Extract rule generation
2016-09-02 00:26:01 +02:00
Patrick Florek
c8bd8db601
# Association rule learning - Apriori algorithm
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* Generating frequent k-length item sets
* Generating rules based on frequent item sets
* Algorithm has exponential complexity, be aware of it
* Apriori algorithm is split into apriori and candidates method
* Second step rule generation is implemented by rules method
* Internal methods are invoked for fine grain unit tests
* Wikipedia's train samples and an alternative are provided for test cases
* Small documentation for public interface is also shipped
2016-08-23 15:44:53 +02:00
Arkadiusz Kondas
3599367ce8
Add docs for neural network
2016-08-14 19:14:56 +02:00
Arkadiusz Kondas
963cfea551
add ClassificationReport docs
2016-07-19 22:17:03 +02:00
Arkadiusz Kondas
7abee3061a
docs for files dataset and php-cs-fixer
2016-07-16 23:56:52 +02:00
Arkadiusz Kondas
7c0767c15a
create docs for tf-idf transformer
2016-07-12 00:21:34 +02:00
Arkadiusz Kondas
ba8927459c
add docs for ConfusionMatrix
2016-07-12 00:11:18 +02:00
Arkadiusz Kondas
bb35d045ba
add docs for Pipeline
2016-07-12 00:00:17 +02:00
Arkadiusz Kondas
ee6ea3b850
create docs for StratifiedRandomSplit
2016-07-11 00:07:07 +02:00
Arkadiusz Kondas
d19490d62a
update docs example
2016-05-31 18:02:30 +02:00
Arkadiusz Kondas
325427c723
update missing docs
2016-05-14 21:30:13 +02:00
Arkadiusz Kondas
ccfa38ba4d
wine and glass demo dataset docs
2016-05-10 23:44:28 +02:00
Arkadiusz Kondas
77647fda45
update readme
2016-05-09 23:52:09 +02:00
Arkadiusz Kondas
365a9baeca
update docs
2016-05-07 23:53:42 +02:00
Arkadiusz Kondas
5950af6072
update and refactor documentation
2016-05-02 13:49:19 +02:00
Arkadiusz Kondas
d2e0ce446c
update classifier docs
2016-04-16 21:41:37 +02:00
Arkadiusz Kondas
6f5f190600
docs for manhattan distance
2016-04-15 22:32:20 +02:00
Arkadiusz Kondas
50fbcddfc4
create docs for distance metrics functions
2016-04-13 21:20:55 +02:00
Arkadiusz Kondas
5be2147784
creat docs files
2016-04-09 00:36:48 +02:00