Sentence examples for splits of the data from inspiring English sources

The main findings are that only 12% of papers use aspect ratios with vertical scale set approximately equal to horizontal scale (vertical exaggeration in the range 0.8 1.2). 75% of papers use reflection seismic with vertical exaggeration greater than 2. Splits of the data in terms of shallow high resolution seismic and deep, crustal imaging seismic were also obtained.

RRegrs was applied with 10 random splits of the data (75%% train and 25%% test) along with 10 Y-randomization runs for the best model.

Ten random splits of the data were performed (75%% train and 25%% test) along with ten Y-randomization runs for the best model.

Table 4 shows the best model selected by RRegrs, its number of features, the adj.R2 and the R2 and RMSE values for the train and test sets, averaged over 10 random splits of the data.

The ENET averaged statistics for 10 splits of the data are ({text{R}}_{text{test}}^{2}) = 0.746, ({text{R}}_{text{CV}}^{2}) = 0.933, which are very similar to the values reported by the authors.

The SVRM averaged statistics for ten splits of the data are ({text{R}}_{text{CV}}^{2}) = 0.556 (10-fold CV), ({text{R}}_{text{test}}^{2}) = 0.537, which are close to the ones reported by the authors when the distance threshold is not applied.

Using other preprocessing methods and multiple random splitting of the data sets obtained the similar results.

The ratio 70-30 is often used in data mining for split of the data set (Analysis Services 2017).

The same splitting of the data into training and external set was used as in the previous publications.

We analysed the variation in the prediction performance that results from choosing a different split of the data.

We use a 70/30 split of the data into training and out-of-sample testing sets, and examine the model performance on 100 random permutations of this split.