The phrase "a particular data set" is correct and usable in written English.
You can use it when referring to a specific collection of data that is being analyzed or discussed.
Example: "In our research, we focused on a particular data set that provided insights into consumer behavior."
Alternatives: "a specific data set" or "a certain data set".
The disadvantage is retaining a large variance of forecast results for a particular data set.
Model comparison tests are used to select from two competing models which best describes a particular data set.
Gamalon's system uses probabilistic programming or code that deals in probabilities rather than specific variables to build a predictive model that explains a particular data set.
A particular data set provided by full scale measurements on the coast guard vessel KV Svalbard during the Winter 2007 was analyzed by means of the present approach.
However not all sites need all of the data in a particular data set, or have the (perhaps specialized) processing capabilities required.
We introduce some methods for determination of the parametric uncertainty of a class of kinetic models for a particular data set.
The response ID denotes which response(s) in the source or background(s) data set(s) to return, in the event that more than one response has been loaded in association with a particular data set.
As there is no theory for deciding which is the most convenient neural network architecture to deal with a particular data set, an experimental study was performed with different numbers of neuron in the hidden layer.
These deviations are observed mainly due to empirical coefficients in the correlations that have been fitted to a particular data set, but without theoretical meaning these coefficients cannot be extrapolated to other foam structures.
Analysis of the performance of PCA and ANNs also lends insight into the localization of useful information within a particular data set, a feature that may be exploited in the selection of experiments for efficient mission design.
As there is no well-developed theory for deciding upon the most convenient neural network architecture to deal with a particular data set, an experimental study was conducted in which ten different architectures with one and two hidden neuron layers and five training algorithms – 50 different options combining network architecture and training algorithm – were compared.
