Scientific Research Publishing

Mineralogical Characterization of Subsurface Soils Using Machine Learning: Application of Support Vector Machines ()

Support vector machines are recognized as a powerful tool for supervised analysis and classification in different fields, particularly geophysics. In summary, SVMs are binary classifiers. Thus, for ...
Game Rant

Best Support Builds in BF6

Marc Santos is a Guides Staff Writer from the Philippines. He's a seasoned writer with over four years of industry experience, and he is an enjoyer of all things difficult in gaming. If Marc's not ...
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Build A Neural Network In Python — Multiclass Classification With Softmax

Hands-on coding of a multiclass neural network from scratch, with softmax and one-hot encoding. #Softmax #MulticlassClassification #PythonAI The 2 House Republicans who voted no on Trump's sweeping ...
Frontiers

Ensemble machine learning prediction accuracy: local vs. global precision and recall for multiclass grade performance of engineering students

1 Department of Computer Science and IT, IIS Deemed to be University, Jaipur, Rajasthan, India 2 Pokhara University, Pokhara, Nepal This study examines the prediction accuracy of ensemble machine ...
IEEE

A SVM Text Classification Approch Based on Binary Tree

Abstract: Support vector machine(SVM ) is based on minimal structure analysis principle, it can it can solve the dimension disaster, regionally minimal problems, etc. But the common SVM can only solve ...
IEEE

A Parallel Multi-Class Classification Support Vector Machine Based on Sequential Minimal Optimization

Abstract: Support vector machine (SVM) is originally developed for binary classification problems. In order to solve practical multi-class problems, various approaches such as one-against-rest (1-a-r) ...