Logger functionality

Logger	Description	Arguments
LoggerIteration	The basic logger to log the current iteration. This one is defined automatically by calling train().	use_as_stopper Boolean to indicate whether this logger should also used as stopping criteria max_iterations Integer value specifying the maximal numbers of iterations
LoggerInbagRisk	Risk logging on the given train dataset.	use_as_stopper Boolean to indicate whether this logger should used as stopping criteria used_loss Loss object that defined the empirical risk eps_for_break Numeric value indicating the relative improvement which is used to stop the algorithm
LoggerOobRisk	Risk logging on a given out of bag dataset.	use_as_stopper Boolean to indicate whether this logger should used as stopping criteria used_loss Loss object that defined the empirical risk eps_for_break Numeric value indicating the relative improvement which is used to stop the algorithm patience Integer defining how many consecutive iterations must fulfill the stopping criteria to finally stop the algorithm oob_data List of Data objects with the out of bag data. Note that a data.frame can be easily transformed by using \(prepareData()</code></dd> <dt><b>oob_response</b></dt> <dd>Response object with the out of bag response. Note that a <code>Response</code> class can be easily created by <code>\)prepareResponse()
LoggerTime	Time logging after each iteration.	use_as_stopper Boolean to indicate whether this logger should used as stopping criteria max_time Integer value specifying the the maximal number of time units time_unit Character value indicating the time unit (possible choices are minutes, seconds, or microseconds)