Sentence examples for dataset mean from inspiring English sources

Principal Component Analysis (PCA) is a transformation of the covariance matrix, and it is defined in (6) as per [23]: C_{ij} = frac{1}{n - 1}mathop sum limits_{m = 1}^{n} left( {X_{im} - bar{X}_{i } } right)left( {X_{jm} - bar{X}_{j} } right) (6 where C = Covariance matrix of PCA transformation; X = dataset value; (overline{X}) = dataset mean; n and m = data length.

After linear interpolation of the filtered geolocation dataset (mean gaps 1.8±4.6 days) the mean track length was 368±139 days (n = 52).

Usually, after quality control step and normalisation of the dataset, mean methylation levels are calculated for each CpG site and are compared between groups of subjects in order to identify significant differences or correlations.

The lack of clinical information relating to diagnoses (e.g., hypertension, CVA) in the EPD and PRCS databases and the lack of information on drug duration, dose or frequency of administration of prescriptions in the TILDA dataset mean that only a limited number of the STOPP criteria applied in the three studies are similar.

For both the training dataset and the test dataset, mean absolute errors of ANN model were lower than those of decision tree model (1819.197 vs. 2782.423, 1162.279 vs. 3424.608) and linear correlation coefficients of the former model were higher than those of the latter (0.955 vs. 0.866, 0.987 vs. 0.806).

In order to prevent this redundant selection of several masses per peak, we grouped mz-values located close to each other (closer than σ p, one fourth of the given peak shape) and, after calculating their mean value, move it uphill the dataset mean spectrum so that it gets in the local maximum of the mean spectrum.

Having full access to Twitter's dataset means that Twitter can offer features Favstar can't, as it has to poll the API.

Simulated changes 2100 2000 of the fractional cover of deciduous woody (top), evergreen woody (middle) and non-woody (bottom) vegetation functional types for a moderate (SRES-B1, normalised to 1961 90 observed CRU dataset means, Echam5 climate change simulations) and a strong climate change scenario (SRES-A2, normalised to 1961 90 observed CRU dataset means, HadCM3 climate change simulations).

The fact that the Pre-diagnosis data was a subset of the full dataset meant that applying the All-data model to Pre-diagnosis observations would have artificially inflated accuracy, due to information leakage between training and test data.

The massive dataset meant that, for a few topics, analysis was restricted to pre-selected portions.

38 Data were formatted as sample (plasma donor) and gene (SGS protein kilodaltons) tables to generate k = 4 clusters using dataset means measured by Euclidean distance.