A Review of Classification Techniques in Machine Learning |
Author(s): |
| Jyoti Pipariya , Acropolis Institute of Technology and Research |
Keywords: |
| Machine Learning, Data Analysis, Machine Learning Algorithms, Supervised Machine Learning, Support Vector Machine |
Abstract |
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The data set used by machine learning algorithms, every instance, is represented using the same set of features. These features may be binary, continuous, and categorical. On the basis of features, it may be classified as supervised and unsupervised learning. If instances are given with known labels which correspond to the correct outputs then the learning is said to be supervised. Whereas unsupervised learning corresponds to the instances which are unlabeled. A special kind of learning called reinforced learning is in which the training information that is provided to the learning system by the external environment is in the form of scalar reinforcement signal. This signal constitutes a measure on the system operation. |
Other Details |
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Paper ID: IJSRDV7I100482 Published in: Volume : 7, Issue : 10 Publication Date: 01/01/2020 Page(s): 597-600 |
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