Input Space Partitioning for Neural Network Learning
نویسندگان
چکیده
Neural Network (NN) is a supervised machine learning technique, which is typically employed to solve classification problems. When solving a classification problem with the conventional NN, the input data fed into the NN often consists of multiple attributes of various properties. However, training the NN with all of the available input attributes may not lead to the desirable performance considering the curse of dimensionality. ABSTRACT
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ورودعنوان ژورنال:
- IJAEC
دوره 4 شماره
صفحات -
تاریخ انتشار 2013