Recent advances of statistics in computational intelligence (RASCI)

• Published in: International journal of machine learning and cybernetics Vol. 9; no. 1; pp. 1 - 3
• Main Authors: Patwary, Muhammed J. A., Liu, James N. K., Dai, Honghua
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 2018; Springer Nature B.V
• Subjects: Accuracy; Artificial Intelligence; Big Data; Classification; Complex Systems; Computational Intelligence; Control; Data mining; Datasets; Documents; Editorial; Electronic commerce; Engineering; Feature selection; Genetic algorithms; Intelligence; Knowledge discovery; Mechatronics; Optimization; Pattern Recognition; Risk assessment; Robotics; Sentiment analysis; Statistical analysis; Statistical methods; Support vector machines; Systems Biology
• ISSN: 1868-8071; 1868-808X
• DOI: 10.1007/s13042-017-0754-9

[...]there has been a major change towards quantitative analysis of statistical methods as well as data through various computational approaches. [...]all the major tasks of computational intelligence can be represented as statistical methods and these methods can be explained from a statistical point of view. [...]to select the feature subsets, improved documents frequency method is used. The experimental results show that the sentiment analysis of Chinese online reviews finds higher accuracy when taking 4-POS-grams as features and it is also reported that low order N-char-grams can achieve better performance than high order N-char-grams features. [...]noteworthy improvement in sentiment analysis of Chinese online reviews can be achieved through improved document frequency.