Tuning the Architecture of Neural Networks for Multi-Class Classification
نویسندگان
چکیده
منابع مشابه
Multi Class Adult Image Classification Using Neural Networks
As the Internet became popular, the volume of digital multimedia data is exponentially increased in all aspects of our life. This drastic increment in multimedia data causes unwelcome deliveries of adult image contents to the Internet. Consequently, a large number of children are wide-open to these harmful contents. In this paper, we propose an efficient classification system that can categoriz...
متن کاملMulti - class Object Classification and Detection Using Neural Networks
Two problems in computer vision are object classification and detection. Object classification is the determination of what category an object belongs to and object detection is the determination of where suspicious objects are in a large picture and what class they belong to. Given the advantageous of an automated recognition system, a solution to this problem has always been a desirable objec...
متن کاملMulti-Step-Ahead Prediction of Stock Price Using a New Architecture of Neural Networks
Modelling and forecasting Stock market is a challenging task for economists and engineers since it has a dynamic structure and nonlinear characteristic. This nonlinearity affects the efficiency of the price characteristics. Using an Artificial Neural Network (ANN) is a proper way to model this nonlinearity and it has been used successfully in one-step-ahead and multi-step-ahead prediction of di...
متن کاملOne-class document classification via Neural Networks
Automated document retrieval and classification is of central importance in many contexts; our main motivating goal is the efficient classification and retrieval of ‘‘interests’’ on the internet when only positive information is available. In this paper, we show how a simple feed-forward neural network can be trained to filter documents under these conditions, and that this method seems to be s...
متن کاملBinary output layer of feedforward neural networks for solving multi-class classification problems
Considered in this short note is the design of output layer nodes of feedforward neural networks for solving multi-class classification problems with r (r ≥ 3) classes of samples. The common and conventional setting of output layer, called “one-to-one approach” in this paper, is as follows: The output layer contains r output nodes corresponding to the r classes. And for an input sample of the i...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of the Korean Operations Research and Management Science Society
سال: 2013
ISSN: 1225-1119
DOI: 10.7737/jkorms.2013.38.1.139