Sentence examples for using the overall dataset from inspiring English sources

In prediction study using the overall dataset containing various IL structures, the six calculated terms (Ec, Sc, Ac, J+, Ea, and Sa) were selected and correlated with the observed toxicity values in R2 of 0.748 for the training set, R2 of 0.711 for the test set and R2 of 0.655 for external validation set.

Furthermore, statistical t-test revealed that classifying PSD features with either SVM or MLP using data from low familiarity music video sessions were significantly better than classifying by the same approach using the overall dataset.

In arousal recognition, the degree of classification above the chance level using only data from unfamiliar song sessions was superior to that using the overall dataset, and the data from familiar song sessions achieved the lowest performance.

Genetic admixture analysis was conducted with Structure using the overall dataset with both cultivated and wild plants, while excluding wild individuals from group B. The four groups (K = 4) observed, corresponding to groups A, C, D, and E, were found to be genetically distinct with either RFLPs or SSRs.

Using the overall combined dataset, we found there were 48 occurrences in 241 individuals with IS compared with 720 occurrences in 4300 individuals in the EA-ESP dataset (P = 0.20).

We calculated the two indicators using first the overall dataset and compared the proportions with those resulting from computation in sub-samples obtained with the three sampling methods.

Similar to the results obtained using our dataset, classifying arousal and valence by using data from unfamiliar music video sessions achieved higher performance than by using either high familiarity sessions or the overall dataset.

In this case, less than 10% of the overall dataset was examined using random sampling.

The dN/dS ratio for the overall dataset was first calculated using the one-ratio model (M0) as implemented in the PAML software (see Materials and Methods).

In order to answer this question, Tree Maps was used to visualize the structural diversity of the scaffolds within the overall dataset.

The final models, fit using a training subset of the data, were cross-validated against both the overall dataset and a holdout subset of the data.