A Quick Negative Selection Algorithm for One-Class Classification in Big Data Era
نویسندگان
چکیده
منابع مشابه
A Fuzzy TOPSIS Approach for Big Data Analytics Platform Selection
Big data sizes are constantly increasing. Big data analytics is where advanced analytic techniques are applied on big data sets. Analytics based on large data samples reveals and leverages business change. The popularity of big data analytics platforms, which are often available as open-source, has not remained unnoticed by big companies. Google uses MapReduce for PageRank and inverted indexes....
متن کاملFeature Selection in Structural Health Monitoring Big Data Using a Meta-Heuristic Optimization Algorithm
This paper focuses on the processing of structural health monitoring (SHM) big data. Extracted features of a structure are reduced using an optimization algorithm to find a minimal subset of salient features by removing noisy, irrelevant and redundant data. The PSO-Harmony algorithm is introduced for feature selection to enhance the capability of the proposed method for processing the measure...
متن کاملNegative Selection Based Data Classification with Flexible Boundaries
One of the most important artificial immune algorithms is negative selection algorithm, which is an anomaly detection and pattern recognition technique; however, recent research has shown the successful application of this algorithm in data classification. Most of the negative selection methods consider deterministic boundaries to distinguish between self and non-self-spaces. In this paper, two...
متن کاملData Source Selection for Information Integration in Big Data Era
In Big data era, information integration often requires abundant data extracted from massive data sources. Due to a large number of data sources, data source selection plays a crucial role in information integration, since it is costly and even impossible to access all data sources. Data Source selection should consider both efficiency and effectiveness issues. For efficiency, the approach shou...
متن کاملMulti-class Classification in Big Data
The paper suggests the on-line multi-class classi er with a sublinear computational complexity relative to the number of training objects. The proposed approach is based on the combining of two-class probabilistic classi ers. Pairwise coupling is a popular multi-class classication method that combines all comparisons for each pair of classes. Unfortunately pairwise coupling su ers in many cases...
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: Mathematical Problems in Engineering
سال: 2017
ISSN: 1024-123X,1563-5147
DOI: 10.1155/2017/3956415