Sentence examples for top performing model from inspiring English sources

The top performing model from the RF classifier produced the highest kappa of 64.8%, improving on the parsimonious LR model kappa by 31.1% with a moderate gain of 6.2% over the county extent model.

While the final features used for the model required only 4 GB, both feature creation and generating the top performing model takes around 48 h.

Results from benchmarking of the protein descriptors revealed that the model built with amino acid composition descriptors was the top performing model with accuracy, sensitivity and specificity in excess of 80% and MCC greater than 0.6 for all three data subsets (e.g. training, tenfold cross-validation and external sets).

The performance of models with homologous sequence reduction set at 99% is shown in Table 3. Again, J48 model built using AAC/DPC/TPC descriptors was the top performing model as assessed via tenfold CV with Ac, Sn, Sp and MCC with 79.40 ± 2.75%, 80.78 ± 1.86%, 77.98 ± 3.20% and 0.59 ± 0.06, respectively, when compared to other J48 models built with different descriptor sets.

For the performance of the sequence homologous reduction at 95%, it can be seen that the top performing model of the tenfold CV set resulted in Ac, Sn, Sp and MCC of 72.13 ± 4.18%, 79.83 ± 3.66%, 61.03 ± 5.34% and 0.42 ± 0.09, respectively, was from the model built using amino acid composition.

Table 11 documents interesting insights into the most relevant features of the top performing model.

We compared the top performing models developed for a smaller, nested experimental extent using RF and LR classifiers, and used the best overall model to produce a predictive map of the spatial distribution of L. sinense across our country-wide study extent.

Precipitation was not present in any of the top performing models for high peak outbreak seasons.

Similar to high peak seasons, precipitation was not present in any of the top performing models for low peak seasons.

For top performing models in low peak seasons, wind speed appears in over 50% of the best models for predictions two weeks in advance and then drops to less than 20% for predictions three weeks in advance.

Maximum relative humidity appears in 51% of models predicting two weeks in advance while minimum relative humidity only appears in 2% of models two weeks out, both have identical representation in predictions three weeks out, appearing only in 22% of the top performing models.