Product Category Classification with Machine Learning
نویسندگان
چکیده
منابع مشابه
ANGEL - Machine Learning Classification
The Automated Network Games Enhancement Layer (ANGEL) project aims to leverage machine learning techniques to automate the classification and isolation of interactive (e.g. games, voice over IP) and noninteractive (e.g. web) traffic. This information is then used to dynamically reconfigure the network to improve the Quality of Service provided to the current interactive traffic flows and subseq...
متن کاملOne-Class Classification with Extreme Learning Machine
One-class classification problemhas been investigated thoroughly for past decades. Among one of themost effective neural network approaches for one-class classification, autoencoder has been successfully applied for many applications. However, this classifier relies on traditional learning algorithms such as backpropagation to train the network, which is quite time-consuming. To tackle the slow...
متن کاملClassification of Solar Wind with Machine Learning
We present a four-category classification algorithm for the solar wind, based on Gaussian Process. The four categories are the ones previously adopted in Xu and Borovsky [2015]: ejecta, coronal hole origin plasma, streamer belt origin plasma, and sector reversal origin plasma. The algorithm is trained and tested on a labeled portion of the OMNI dataset. It uses seven inputs: the solar wind spee...
متن کاملCategory Learning by Inference and Classification
The nature of category formation is linked to the tasks applied to learn the categories. To explore this idea, we investigated how three different methods of category learning—Classification Learning, Inference Learning, and Mixed Learning (a mixture of the two)—affect the way people form categories. In Classification Learning, subjects learned categories by predicting the class to which an ind...
متن کاملLearning Multi-category Classification in Bayesian Framework
We propose an algorithm for Sparse Bayesian Classification for multi-class problems using Automatic Relevance Determination(ARD). Unlike other approaches which treat multiclass problem as multiple independent binary classification problem, we propose a method to learn the multiclass predictor directly. The usual approach of “one against rest” and “pairwise coupling” are not only computationally...
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: Sakarya University Journal of Computer and Information Sciences
سال: 2019
ISSN: 2636-8129
DOI: 10.35377/saucis.02.01.523139