technologies. We integrate patent big data for technological integration and use text mining, boosting, and ensemble for integrated … technologies and analyze the integrated patent data using regression trees, random forest, extreme gradient boosting, and ensemble …

enzyme ensemble of source and sink superadditivity and subadditivity by mixing or structured transfer (compartmentalization … will be earning superadditivity of the ensemble of both will be observed. Such conditions characterize symbiosis and … sink. Subadditivity will appear within the ensemble when the substrate will be more costing or less earning after the …

focus on improving MF-based recommender's accuracy by homogeneous ensemble methods. To build such ensembles, we investigate …, and then the effective methods are combined to form a cascade MF ensemble scheme. The validation results on experiment … datasets demonstrate that compared to a single MF-based recommender, our ensemble scheme could obtain a significant improvement …

degree including charity can be understood within the ensemble concept. In an ensemble transfer of substrate from a source to … a sink may result in superadditivity as well as subadditivity. The ensemble with the better net profit will prevail …

The ensemble is a new entity on a higher level of complexity composed of source and sink. When substrate is transferred … the ensemble. The combined and interdependent productivity of the ensemble forms a surface similar to the Cobb …. Source and sink form a harmonic ensemble. When source and sink use the same substrate there will be competition. The surface …

We propose a new ensemble classification algorithm, named super random subspace ensemble (Super RaSE), to tackle the … sparse classification problem. The proposed algorithm is motivated by the random subspace ensemble algorithm (RaSE). The RaSE …

performance in its simulation of this MCV event. Finally, an ensemble of 20 forecasts using mesoscale model MM5 with horizontal … examination of the ensemble spread as well as the correlations between different forecast variables among ensemble members. It is … shown that after MCV development, the ensemble mean performs poorly while individual ensemble members with good forecasts of …