In this work, we have considered the ensemble of classifier chains (ECC) algorithm in order to solve the multi-label classification (MLC) task. It starts from binary relevance algorithm (BR), a simple and direct approach to MLC that has been shown to provide good results in practice. ...
The performance of the proposed ensemble method is measured using 10-fold cross-validation. Each data set is randomly divided into ten subsets with an approximately equal number of polypeptide chains. Each classifier is trained and tested ten times with one dataset. And for each time, nine subset...
Knowledge of protein-protein interactions and their binding sites is indispensable for in-depth understanding of the networks in living cells. With the avalanche of protein sequences generated in the postgenomic age, it is critical to develop computation
these basics models perform not so well by themselves either because they have a high bias (low degree of freedom models, for example) or because they have too much variance to be robust
the evolutionary features are not easy to get due to the limitation of computing power, so the predictors were developed mainly based on either structure information or sequence features, or a combination of them. For instance, the Support Vector Machine (SVM) classifier developed by Ahmad et al...
Prediction of protein-protein interaction sites is one of the most challenging and intriguing problems in the field of computational biology. Although much progress has been achieved by using various machine learning methods and a variety of available fe
the evolutionary features are not easy to get due to the limitation of computing power, so the predictors were developed mainly based on either structure information or sequence features, or a combination of them. For instance, the Support Vector Machine (SVM) classifier developed by Ahmad et al...
In this work, we have considered the ensemble of classifier chains (ECC) algorithm in order to solve the multi-label classification (MLC) task. It starts from binary relevance algorithm (BR), a simple and direct approach to MLC that has been shown to provide good results in practice. ...
Bracha ShapiraSpringer, Berlin, HeidelbergInternational Workshop on Multiple Classifier SystemsLena Tenenboim-Chekina, Lior Rokach, and Bracha Shapira. Ensemble of feature chains for anomaly detection. In Multiple Classifier Systems, pages 295-306. Springer, 2013....
Further- more, our group designed DM-RPIs, a classifier that integrated SVM, RF, and CNN to classify ncRPIs by learning the discriminative features from 3-mer and 4-mer frequency of proteins and ncRNAs, respectively [30]. In addition, LightGBM, rpiCOOL, RPIFSE, RPI-SAN, and LPI-CNNCP...