Evaluating explorative prediction power of machine learning algorithms for materials discovery using k-fold forward cross-validation
… predictor should achieve high exploration accuracy. On the other hand, predictors that cannot
predict … then split into three sets – first 10%, middle 80%, and last 10%. The middle set is …
predict … then split into three sets – first 10%, middle 80%, and last 10%. The middle set is …
UFold: fast and accurate RNA secondary structure prediction with deep learning
… over time, reaching a performance ceiling of about 80% (32). It … HIT 80 to remove any
sequences that have similarity over 80% … UFold can achieve a similar performance on …
sequences that have similarity over 80% … UFold can achieve a similar performance on …
RNA secondary structure prediction using an ensemble of two-dimensional deep neural networks and transfer learning
… Obtaining functional clues for noncoding RNAs requires accurate base-pairing or
secondary-structure prediction… sequences with annotated secondary structure from bpRNA 34 at …
secondary-structure prediction… sequences with annotated secondary structure from bpRNA 34 at …
RNA secondary structure prediction using deep learning with thermodynamic integration
K Sato, M Akiyama, Y Sakakibara - Nature communications, 2021 - nature.com
… secondary structure prediction from single sequences, and our method, which is able to achieve
high accuracy … EST 44 , with a cutoff threshold of 80%, and discarded sequences whose …
high accuracy … EST 44 , with a cutoff threshold of 80%, and discarded sequences whose …
[HTML][HTML] Highly accurate protein structure prediction with AlphaFold
… accurate end-to-end structure prediction, a new equivariant attention architecture, use of
intermediate losses to achieve iterative refinement of predictions… fewer than 80 amino acids had …
intermediate losses to achieve iterative refinement of predictions… fewer than 80 amino acids had …
Improving prediction of protein secondary structure, backbone angles, solvent accessibility and contact numbers by using predicted contact maps and an ensemble of …
… to achieving high performance for the accuracy of predicting … model, we performed 10-fold
Cross Validation (CV) on our … the 10 folds) against Model 0’s performance on the Validation …
Cross Validation (CV) on our … the 10 folds) against Model 0’s performance on the Validation …
Predicting protein structural classes for low-similarity sequences by evaluating different features
… through grid search with 10-fold cross validation in the LibSVM … that the maximum accuracy
was achieved by combining … feature for protein structural class prediction. Comparative …
was achieved by combining … feature for protein structural class prediction. Comparative …
Easy and accurate protein structure prediction using ColabFold
… made significant strides toward achieving this goal. AlphaFold2 … capable of producing protein
structure predictions nearly … In addition, through 16 iterations, a total of 80 predicted protein …
structure predictions nearly … In addition, through 16 iterations, a total of 80 predicted protein …
Combination of Support Vector Machine and K-Fold cross validation to predict compressive strength of concrete in marine environment
H Ling, C Qian, W Kang, C Liang, H Chen - Construction and Building …, 2019 - Elsevier
… built to compare the prediction precision with SVM model. … In the dataset, 80 groups of data
were employed as the … and lower the difficulty of obtaining wanted papers, the parameter of …
were employed as the … and lower the difficulty of obtaining wanted papers, the parameter of …
Short-Term Photovoltaic Power Output Prediction Based on k-Fold Cross-Validation and an Ensemble Model
R Zhu, W Guo, X Gong - Energies, 2019 - mdpi.com
… The k-fold cross-validation method can effectively improve the … can achieve higher prediction
accuracy than a single model. … selected 80% of the samples as the training set and 10% of …
accuracy than a single model. … selected 80% of the samples as the training set and 10% of …