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Operating Systems AIX [Opinion] A Public Answer To Rob McNelly Post 302976083 by MadeInGermany on Thursday 23rd of June 2016 02:54:29 PM
Old 06-23-2016
Quote:
I have worked in the *NIX world since 1981, over that time I have watched the skill level of the sysadmin degrade, a lot of it revolves around training – my first “Sysadmin I” course was five weeks long and I never actually saw a machine. It was all spent sitting at a Wyse 30 terminal, with a number of other trainees. Now I see sysadmins working for major vendors, with no training whatsoever.
Oh, you missed 11 exciting yearsSmilie
There is a strong believe that a new style of IT (cloud, virtualization, orchestration, automation, auto-scaling, self-healing, ...) will obsolete traditional system administration. Instead management-by-click will emerge.
Just order your desired IT-functions on your smartphone, and voila - your new company can go!
 

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FANN_CASCADETRAIN_ON_DATA(3)						 1					      FANN_CASCADETRAIN_ON_DATA(3)

fann_cascadetrain_on_data - Trains on an entire dataset, for a period of time using the Cascade2 training algorithm

SYNOPSIS
bool fann_cascadetrain_on_data (resource $ann, resource $data, int $max_neurons, int $neurons_between_reports, float $desired_error) DESCRIPTION
The cascade output change fraction is a number between 0 and 1 determining how large a fraction the fann_get_MSE(3) value should change within fann_get_cascade_output_stagnation_epochs(3) during training of the output connections, in order for the training not to stagnate. If the training stagnates, the training of the output connections will be ended and new candidates will be prepared. This training uses the parameters set using the fann_set_cascade_..., but it also uses another training algorithm as it's internal train- ing algorithm. This algorithm can be set to either FANN_TRAIN_RPROP or FANN_TRAIN_QUICKPROP by fann_set_training_algorithm(3), and the parameters set for these training algorithms will also affect the cascade training. PARAMETERS
o $ann -Neural network resource. o $data -Neural network training data resource. o $max_neurons - The maximum number of neurons to be added to neural network. o $neurons_between_reports - The number of neurons between printing a status report. A value of zero means no reports should be printed. o $desired_error - The desired fann_get_MSE(3) or fann_get_bit_fail(3), depending on which stop function is chosen by fann_set_train_stop_func- tion(3) RETURN VALUES
Returns TRUE on success, or FALSE otherwise. SEE ALSO
fann_train_on_data(3), fann_cascadetrain_on_file(3). PHP Documentation Group FANN_CASCADETRAIN_ON_DATA(3)
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