I am modeling the popular German credit data using, Decision Trees, Support Vector Machines as standalone classifiers, the homogeneous ensemble of SVMs and random forest and, finally, the ensemble of Support Vector Machines and Decision Tree. The motivation is to establish that heterogeneous ensembles are better predictors than the homogeneous ensemble.
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I plan to use ensemble partial least squares or Deep Neural Network Relevant Skills and Experience I participated in IBM Research Africa in Machine learning hackathon with accepted abstracts in Deep Learning Proposed Daha Fazla
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