* 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
* correct CalcDCG in rank_metric.cc
DCG use log base-2, however `std::log` returns log base-e.
* correct CalcDCG in rank_obj.cc
DCG use log base-2, however `std::log` returns log base-e.
* use std::log2 instead of std::log
make it more elegant
* use std::log2 instead of std::log
make it more elegant
* 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
