DataHub v1 is the original DataHub catalog of 11,000+ open datasets, now migrated to PortalJS Arc.
Dataset

Evaluation of College Scientific Research Capacity of Based on Support Vector Machine

College scientific research capacity is the core capability for the college, and it has many factors affecting college research capacity. Selecting 11 typical indicators, an evaluation model of college scientific research capacity and algorithm based on support vector machine is introduced. Firstly, support vector…

About

College scientific research capacity is the core capability for the college, and it has many factors affecting college research capacity. Selecting 11 typical indicators, an evaluation model of college scientific research capacity and algorithm based on support vector machine is introduced. Firstly, support vector machine is introduced in brief; secondly, a new evaluation model based on support vector machine is established; at last, an algorithm for evaluation model based on the support vector machine is proposed. On this basis, the support vector machine algorithm for evaluation model is realized with MATLAB. 25 raw data areculled for the simulation experiments, in which 20 is considered as a training set, and other 15 as the testing set. Simulation results show that the rateof correct classification for the algorithm is 100%, so the algorithm achieves the desired goal. http://www.erfrontier.org/paperInfo.aspx?ID=664

Download & API
Evaluation of College Scientific Research Capacity of Based on Support Vector Machineaspx28 KB
College scientific research capacity is the core capability for the college, and it has many factors affecting college research capacity. Selecting 11 typical indicators, an evaluation model of college scientific research capacity and algorithm based on support vector machine is introduced. Firstly, support vector machine is introduced in brief; secondly, a new evaluation model based on support vector machine is established; at last, an algorithm for evaluation model based on the support vector machine is proposed. On this basis, the support vector machine algorithm for evaluation model is realized with MATLAB. 25 raw data areculled for the simulation experiments, in which 20 is considered as a training set, and other 15 as the testing set. Simulation results show that the rateof correct classification for the algorithm is 100%, so the algorithm achieves the desired goal.
Download
Sources & license
License
  • Other (Open)