Sentence examples for model performed poor from inspiring English sources

However, the frequency-based model performed poor in this dataset as well [Additional file 7: Table S6].

Figure  2 shows an example of a short cyclic peptide (10 residues) where PEPstrMOD approached close to the native structure while the ab initio model performed poor.

For a couple of countries (Italy and the Netherlands), however, the autoregressive model performed poorer than the base non-linear model.

Similarly, Rfam-based covariance models performed poor to classify the novel/non-similar sequences whereas comparatively structural information based graph-properties of RNAcon method performed well because graph-properties based features provide both local as well as global structural features of a particular class.

These models perform poor with MCC 0.27, when evaluated on Pyrimidine class of molecules.

It is a well-known fact that machine learning techniques, particularly SVM-based models perform poor especially when positive and negative dataset is unbalanced.

The non-robust error model performs the poorest with log(lake) being non-significant and rnegative being significant only at 10%% level.

However, power performed poorer than theta band functional connectivity in terms of specificity and sensitivity in our regression models, indicating the added value of connectivity over power.

Again the models performed slightly poorer than the full, data-driven model in the ECRIC dataset, but somewhat better in the WMCIU validation dataset.

Thus, they generally perform poor performance on the imbalanced datasets.

This model performed better, with a good sensitivity of 74% but a poor specificity of 66%.