Optimal Map classification with uncertainty information
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Updated
Nov 8, 2017 - C#
Optimal Map classification with uncertainty information
Sample-based learning implementation to classify answers of open questions in surveys (Semantic Field) given a .csv with seed words.
A desktop application by using WEKA library (C# application for WEKA.dll) to obtain the suitable dataset content for each classification algorithm. In the app, 11 decision support system algorithms and machine learning were used.
Microsoft Outlook automatic Spam Classifier, Classify emails as they arrive and move them to your own folders. Works on Office 356, Outlook 2016,2013 and 2010
Learning Algorithms Homework
you can learning operating midwife in operate room in VR hospital within AI robots for the first time in all around the world
Machine learning library for classification tasks
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