The phrase "algorithmic training" is correct and usable in written English.
It can be used in contexts related to machine learning, data science, or any field that involves training algorithms to perform specific tasks.
Example: "The researchers focused on algorithmic training to improve the accuracy of their predictive models."
Alternatives: "algorithm training" or "training algorithms".
But how can legal protections be safeguarded if decisions are automated by algorithmic models trained on discrete data-sets — or flowing from policies administered by being embedded on a blockchain?
But all the while the machine learning is running in the background, learning and getting better — and as soon as it becomes as good as the humans the system is switched to being powered by the now trained algorithmic eye, with humans left to do only periodic (sanity) checks.
The WSJ reported on Monday that employees of Gmail app developer Edison Software personally read the emails of hundreds of users to build a new feature; employees of another developer, Return Path Inc, reportedly read about 8,000 unredacted user emails to help train algorithmic software.
Ideally, as more countries gain the capacity to run their own FELTPs, there will be an algorithmic growth of trained professionals in the region.
Capacity z scores become significantly more limited from the first day (Day 1) to the last day (Day 8) of training for both algorithmic fusion [ t(17)=3.03, p<.05, d=1.02] and cognitive fusion [ t(17)=2.99, p<.05, d=0.49].
Three different methodologies are traditionally followed to cope with this problem [3, 13]: data level solutions that rebalance the training set [10], algorithmic level solutions that adapt the learning stage towards the minority classes [11] and cost-sensitive solutions which consider different costs with respect to the class distribution [12].
The 'Product of Experts' architecture (concentrating on binary-stochastic elements) is described in the context of its suitability for implementation as mixed-mode hardware, with algorithmic modifications that render the training procedure hardware-implementable. Results show that the PoE is capable of modelling non-linear, multi-dimensional data drawn from both artificial and real sources.
After the completion of the training process, the algorithmic SVM model would be 'fixed' for further running.
Considering that application of an algorithmic approach involves a short course training, especially for nurses and inexperienced personnel, future studies should assess which logical approach is the most effective for a given amount of training [ 23].
