Recognition of Control Chart Pattern Using Improved Supervised Locally Linear Embedding and Support Vector Machine
نویسندگان
چکیده
منابع مشابه
Classification of handwritten digits using supervised locally linear embedding algorithm and support vector machine
The locally linear embedding (LLE) algorithm is an unsupervised technique recently proposed for nonlinear dimensionality reduction. In this paper, we describe its supervised variant (SLLE). This is a conceptually new method, where class membership information is used to map overlapping high dimensional data into disjoint clusters in the embedded space. In experiments, we combined it with suppor...
متن کاملSupervised Locally Linear Embedding Algorithm for Pattern Recognition
The dimensionality of the input data often far exceeds their intrinsic dimensionality. As a result, it may be difficult to recognize multidimensional data, especially if the number of samples in a dataset is not large. In addition, the more dimensions the data have, the longer the recognition time is. This leads to the necessity of performing dimensionality reduction before pattern recognition....
متن کاملSupervised Locally Linear Embedding
Locally linear embedding (LLE) is a recently proposed method for unsupervised nonlinear dimensionality reduction. It has a number of attractive features: it does not require an iterative algorithm, and just a few parameters need to be set. Two extensions of LLE to supervised feature extraction were independently proposed by the authors of this paper. Here, both methods are unified in a common f...
متن کاملAn Effective and Novel Weighted Support Vector Machine Method for Control Chart Pattern Recognition
Control chart pattern recognition is the method to realize quality online monitoring and diagnosis of production process. For the conditions that the number of existing normal mode products is much higher than the abnormal ones during the actual manufacturing process, we proposed a method about WSVM (Weighted Support Vector Machines) for dynamic process of abnormal pattern recognition based on ...
متن کاملControl chart pattern recognition using semi-supervised learning
This paper presents a semi-supervised learning algorithm for a control chart pattern recognition system. A learning neural network is trained with labeled control chart patterns based on unsupervised learning. We then use the classification method based on a statistical correlation coefficient approach to test patterns. We find that the proposed semi-supervised learning algorithm is effective a...
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: Procedia Engineering
سال: 2017
ISSN: 1877-7058
DOI: 10.1016/j.proeng.2017.01.138