GitLab

* warning on categorical feature with sparse values

* [docs] categorical features note

* pass params to predictor

* hotfix

* added test for pandas label of Dataset

* fix when label type is pandas DataFrame; document possible pandas Series type

* fix ndcg group

* fix ndcg

* pass params to _InnerPredictor in train and cv

* fixed verbosity param description

* treat silent param as Fatal log level

* create Dataset in refit method silently

* do not overwrite verbose param by silent argument

* use kwargs in tree plotting functions

* relaxed version

* added possibility to predict numpy array with nrow > max_int32

* save memory more efficient

* better variable name

* added possibility to predict scipy.sparse.csr matrix with nrow > max_int32

* added possibility to predict scipy.sparse.csc matrix with nrow > max_int32

* reworked numpy array case

* bring consistency and clearness into early_stopping_rounds desc, metric desc and implementation

* hotfix

* hotfix

* used NDCG as default metric for lambdarank task

* fixed missed methods at ReadTheDocs and changed default eval_metric

* leaved only unique metrics

* fixed comment

* added NumberOfTotalModel and NumModelPerIteration to C_API and python-package

* fixed tests

* added tests for current_iteration, num_trees, num_model_per_iteration methods

* break huge line in test

* hotfix

* add support of refit-decay

* add refit into c_api

* add test

* update document

* Update basic.py

* Update test_engine.py

* Update basic.py

* Update test_engine.py

* fix comments

* update test

* fix the comments

* Update test_engine.py

* add start_iteration in model saving

* fix test

* shuffle models ability

* fix bug

* update document

* refine

* Update engine.py

* Update basic.py

* fix comments

* fix comment

* refined num_iteration argument in python

* hotfix

* broadcast info about negative values in categorical features to python package

* update link to categorical_feature parameter

* refined random_state description

* use neutral alias and fixed desc of eval_at param, since metric can be not only ndcg

* simplified checks

* consider verbose alias

* fixed declaring function every loop iteration

* added new aliases for params

* run helper/parameter_generator.py

* removed useless test

* ignore vim temporary files

* add importance_type arg to sklearn API

* update documentation info

* remote a trailing space

* remove trailing space (again :))

* add instructions on importance choices to sklearn API

* drop mention of constructor in the feature type setting

* adding a test for different feture types

* remove trailing spaces, make shorter assert in feature importance type handling test

* fixing style issue introduced with the new test

* [python] dont format string values with precision

* indent

* use compat.string_type

* remove parentheses

* removed excess import

* added tests for plotting trees in Python

* refined module_INSTALLED mechanism

* added note about that create_tree_digraph is better than plot_tree

* fixed grammar

* fixed params description in graph plotting functions

* clarified types of attributes in their descriptions

* increased readability of graphs by adding spaces

* added precision parameter to plot tree functions

* added missed description of plot_example in python_guide folder and fixed consistency for packages naming

* more reliable OS detection

* fixed grammar

* made pylint happy

The document of `early_stopping_rounds` says it will check all of
eval_set. But, this is not true. It doesn't check the dataset
specified as the training data.

This change appends an extra phrase "except the training data" to all
of the sentences "If there's more than one, will check all of them" in
documents.

* added checks for categorical features > max_int32

* added tests

* fixed pylint

* removed warnings about overridden categorical features

* Revert "removed warnings about overridden categorical features"

This reverts commit 289a426c700ce8934a526cc456a1b1cd5c621db9.

* a little bit more efficient checks

* added notes about max values in categorical features

* Revert "a little bit more efficient checks"

This reverts commit bed88830243da21a2db454873c0e308126e05732.

* Revert "fixed pylint"

This reverts commit a229e1563b0abc1b13de6358577abf90bd529015.

* Revert "added tests"

This reverts commit 299e001b7550111555b80730d673d4f225cf5f74.

* Revert "added checks for categorical features > max_int32"

This reverts commit 2cc7afacde7c6366644f6988ccedc344752b68c7.

* Clarify docs for feval

* docs- adds that feval can be a string

* docs- deletes extraneous space

* decode error description

* added break line char in log massages