Sentence examples for splitting of data from inspiring English sources
Oracle Partitioning is the splitting of data sets into separate physical files using separate partition table spaces.
Pig Latin shell behaves similar to SQL structure and can speed up the MapReduce operations, by grouping, filtering and splitting of data.
In this case, multiple iterations of the model selection procedure are performed by varying the splitting of data over the training, validation, and test sets [4].
In this paper, we introduce a novel framework that implements SQL-like Hadoop ecosystems, incorporating Pig Latin with the additional splitting of data.
The splitting of data into training, validation and test subsets was carried out to estimate the performance of the neural network for prediction of "unseen" data that were not used for training.
The here described concept of a splitting of data processing into two sub-channels implemented into the parallel working chips, the chips synchronization and the automatization of internal processing management, together with the fully pipelined AHDL code became the framework for the further implementation in the environmental condition of the Argentinian pampa.
The following three definitions describe the horizontal split of data by implementing the grouping method of equivalency in MDSBA.
However, the reality is that we work in a non-asymptotic environment and, furthermore, different splits of data between the folds may produce different optimal tuning parameters.
Adaptive Fuzzy Partition (AFP) modelling used a binary split of data, (sensitisers and non-sensitisers) in which only those compounds classed as "NC" in the original data were deemed to be non-sensitisers.
In this paper, we compare the traditional approach of a single split of data into a training set (for classification) and test set (for accuracy assessment), to a resampling framework where the classification and accuracy assessment are repeated many times.
We found that regardless of resampling design, a single split of data into training and test sets results in a large variance in estimates of accuracy and mapped area.
