* [CORE] allow updating trees in an existing model
* [CORE] in refresh updater, allow keeping old leaf values and update stats only
* [R-package] xgb.train mod to allow updating trees in an existing model
* [R-package] added check for nrounds when is_update
* [CORE] merge parameter declaration changes; unify their code style
* [CORE] move the update-process trees initialization to Configure; rename default process_type to 'default'; fix the trees and trees_to_update sizes comparison check
* [R-package] unit tests for the update process type
* [DOC] documentation for process_type parameter; improved docs for updater, Gamma and Tweedie; added some parameter aliases; metrics indentation and some were non-documented
* fix my sloppy merge conflict resolutions
* [CORE] add a TreeProcessType enum
* whitespace fix
* add support for tweedie regression
* added back readme line that was accidentally deleted
* fixed linting errors
* add support for tweedie regression
* added back readme line that was accidentally deleted
* fixed linting errors
* rebased with upstream master and added R example
* changed parameter name to tweedie_variance_power
* linting error fix
* refactored tweedie-nloglik metric to be more like the other parameterized metrics
* added upper and lower bound check to tweedie metric
* add support for tweedie regression
* added back readme line that was accidentally deleted
* fixed linting errors
* added upper and lower bound check to tweedie metric
* added back readme line that was accidentally deleted
* rebased with upstream master and added R example
* rebased again on top of upstream master
* linting error fix
* added upper and lower bound check to tweedie metric
* rebased with master
* lint fix
* removed whitespace at end of line 186 - elementwise_metric.cc
* Fix typos and messages in docs
* parameter.md: Add docs for updater_seq
Mention the updater_seq parameter which sets the order of the tree
updaters to run and also specifies which ones to run. This can be
useful when pruning is not required or even a custom plugin is
being built along with xgboost.
The `cd ..;` in the one liner takes you up a directory instead of into the xgboost directory. This will cause that step of the installation to fail. It seems like you are meant to enter the xgboost directory as you did in the instructions for installing xgboost without openmp.
* bump up to scala 2.11
* framework of data frame integration
* test consistency between RDD and DataFrame
* order preservation
* test order preservation
* example code and fix makefile
* improve type checking
* improve APIs
* user docs
* work around travis CI's limitation on log length
* adjust test structure
* integrate with Spark -1 .x
* spark 2.x integration
* remove spark 1.x implementation but provide instructions on how to downgrade
* Fixed OpenMP installation on MacOSX with gcc-6
- Modified makefile from gcc-5 to gcc-6
- Removed deprecated install instructions from doc (gcc-5 was automatically forced if available in makefile on OSX)
* Fixed OpenMP installation on MacOSX with gcc-6
- Modified makefile from gcc-5 to gcc-6
- Removed deprecated install instructions from doc (gcc-5 was automatically forced if available in makefile on OSX)
make math better, specifically, unify the notation for Theta or theta. changed basic linear model notation from weight w to theta to make more consistent. Changed Obj function notation also
* Add deviance metric for gamma regression
* Simplify the computation of nloglik for gamma regression
* Add a description for gamma-deviance
* Minor fix
* Add support for Gamma regression
* Use base_score to replace the lp_bias
* Remove the lp_bias config block
* Add a demo for running gamma regression in Python
* Typo fix
* Revise the description for objective
* Add a script to generate the autoclaims dataset
