The phrase "a very large data" is not correct in standard written English.
The correct form should be "a very large amount of data" or simply "very large data" without the article "a."
Example: "The research team collected a very large amount of data for their study."
Alternatives: "a vast amount of data" or "a significant volume of data."
First, with LSPIA, a very large data set can be fitted efficiently and robustly.
The training process uses unlabelled data to pre-train Stacked Sparse Autoencoders, before fine-tuning on labelled data; reducing the need for a very large data set.
I was able, with significant effort, to deploy a wide range of techniques in Python, pandas, CartoDB, matplotlib, and Leaflet in the context of a very large data set from NYC TLC.
Compared to the LOO method, 5-fold cross-validation method or the independent test method requires much less time for the SVM model optimization and it is impossible to do a LOO cross-validation for a very large data set.
This is due to the fact that each high-resolution mouse brain image is a very large data set and it is a multiclass classification problem with extremely imbalanced data size for different classes.
We fit our model to a very large data set to explore whether our model can extract the unique impact of demographics and those of the two types of mail on the two aspects of donation behavior.
"It demonstrates that a combination large numbers of online human volunteers can accomplish the analysis of a very large data-set that would be otherwise intractable".
The main strength of our analysis lies in the availability of a very large, data-rich dataset.
This method could be a challenge for very large data intensive systems.
However, the simulation may also present some problems, e.g., a generation of potentially very large data sets, a high consumption of time, error prone outputs and temporal restrictions [22].
This leads to reduced statistical power compared to character-based methods such as maximum likelihood or Bayesian methods of tree reconstruction, the advantage being a much higher computational efficiency, an important issue for very large data sets.
