College data analysis based on multi-learning method

This paper proposes a new approach to data analysis based on multi-learning method. The proposed method employs a combination of principal component analysis, K-means clustering, random forest, deep neural network and Jack Philips ROI evaluation model, and is effective in solving the problem of choosing donation recipients. Results are validated through data envelop analysis and are believed to accurately reflect the reality. This research can be helpful to analyses of large scale economic problems.

[1]  Xin Zhang,et al.  Modeling of nonlinear system based on deep learning framework , 2016 .

[2]  Financial Incentives and Educational Investment: The Impact of Performance-Based Scholarships on Student Time Use , 2013 .

[3]  R. Murnane Interpreting the Evidence on School Effectiveness , 1981, Teachers College Record: The Voice of Scholarship in Education.

[4]  Wang Feng,et al.  Online Learning Algorithms for Big Data Analytics: A Survey , 2015 .

[5]  Zhang Yi,et al.  Big Data Analysis by Infinite Deep Neural Networks , 2016 .

[6]  Chris Baumann,et al.  School discipline, investment, competitiveness and mediating educational performance , 2017 .

[7]  Xingsheng Gu,et al.  Double global optimum genetic algorithm–particle swarm optimization-based welding robot path planning , 2016 .

[8]  B. S. Mahanand,et al.  Predicting popularity of online articles using Random Forest regression , 2016, 2016 Second International Conference on Cognitive Computing and Information Processing (CCIP).

[9]  Feiping Nie,et al.  Re-Weighted Discriminatively Embedded $K$ -Means for Multi-View Clustering , 2017, IEEE Transactions on Image Processing.

[10]  Hsin-Cheng Huang,et al.  Regularized Principal Component Analysis for Spatial Data , 2015, 1501.03221.

[11]  Chuan Ding,et al.  Prioritizing Influential Factors for Freeway Incident Clearance Time Prediction Using the Gradient Boosting Decision Trees Method , 2017, IEEE Transactions on Intelligent Transportation Systems.

[12]  Fengxia Dong,et al.  Measuring farm sustainability using data envelope analysis with principal components: the case of Wisconsin cranberry. , 2015, Journal of environmental management.

[13]  Cheng Xueqi,et al.  Survey on Big Data System and Analytic Technology , 2014 .