Top

Evolutionary Intelligence

Published in:

30-04-2020 | Special Issue

Construction of cascaded depth model based on boosting feature selection and classification

Authors: Hongwen Yan, Zhenyu Liu, Qingliang Cui

Published in: Evolutionary Intelligence | Issue 4/2022

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

Artificial intelligence is an important research direction in the field of computer science. Its vision is to better understand the world around us. In this paper, the specific feature transformation, feature selection and classifier algorithm used in the framework are studied and analyzed, and a cascade depth model is constructed. Through detailed analysis of the feature transformation, feature selection and classification methods used in the framework, an effective cascade depth model based on feature extraction and feature selection is successfully implemented, and the effectiveness of the proposed feature combination method is verified.

previous article Neural multi-task collaborative filtering

next article Research and application of AHP-fuzzy comprehensive evaluation model

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Bengio Y, Courville A, Vincent P (2013) Representation learning: a review and new perspectives. IEEE Trans Pattern Anal Mach Intell 35(8):1798–1828CrossRef

Forsyth D (2015) Representation learning. Computer 48(4):6CrossRef

Peng X, Wang L, Qiao Y et al (2014) Boosting VLAD with supervised dictionary learning and high-order statistics. In: European conference on computer vision, vol 6891. Springer, Cham, pp 660–674

Baldassi C, Ingrosso A, Lucibello C et al (2015) Subdominant dense clusters allow for simple learning and high computational performance in neural networks with discrete synapses. Phys Rev Lett 115(12):128101CrossRef

Zhao S, Zhang Y, Xu H (2019) Feature selection and stability evaluation based on paired constraint partition. Comput Digital Eng 47(6):1441–1445

Yan H, Lu J, Zhou X (2014) Prototype-based discriminative feature learning for kinship verification. IEEE Trans Cybern 45(11):2535–2545CrossRef

Xia DX, Su SZ, Geng LC et al (2017) Learning rich features from objectness estimation for human lying-pose detection. Multimed Syst 23(4):515–526CrossRef

Zhao Q, Ge SS, Ye M et al (2016) Learning saliency features for face detection and recognition using multi-task network. Int J Soc Robot 8(5):709–720CrossRef

Sheng W, Siqi S, Zhen L et al (2017) Accurate de novo prediction of protein contact map by ultra-deep learning model. PLoS Comput Biol 13(1):e1005324CrossRef

10.

Han Z, Wei B, Zheng Y et al (2017) Breast cancer multi-classification from histopathological images with structured deep learning model. Sci Rep 7(1):4172CrossRef

11.

Zhong SH, Liu Y, Li B, Long J (2015) Query-oriented unsupervised multi-document summarization via deep learning model. Expert Syst Appl 42(21):8146–8155CrossRef

12.

Chen C, Liang X (2019) Feature selection method based on Gini index and Chi square test. Comput Eng Des 8:2342–2345

13.

Qi C, Zhou Z, Sun Y et al (2016) Feature selection and multiple kernel boosting framework based on PSO with mutation mechanism for hyperspectral classification. Neurocomputing 220:181–190CrossRef

14.

Guo NR, Li THS (2011) Construction of a neuron-fuzzy classification model based on feature-extraction approach. Expert Syst Appl 38(1):682–691CrossRef

15.

Guo Y, Liu S, Li Z et al (2018) BCDForest: a boosting cascade deep forest model towards the classification of cancer subtypes based on gene expression data. BMC Bioinform 19(S5):118CrossRef

16.

Sun Y, Zhang X, Sun L (2019) Feature selection method based on k-medoids clustering and neighborhood distance. Comput Appl Res 8:2279–2283

17.

Wang J-J, Xue F, Li H (2015) Simultaneous channel and feature selection of fused EEG Features Based on sparse group lasso. Biomed Res Int 2015:1–13

18.

Chen P, Pan C (2018) Diabetes classification model based on boosting algorithms. BMC Bioinform 19(1):109MathSciNetCrossRef

19.

Li S, Zhang Z, Yang X (2019) An optimization study of feature selection parameters based on cloud model. Comput Technol Dev 3

20.

Shi H, Li H, Zhang D et al (2018) An efficient feature generation approach based on deep learning and feature selection techniques for traffic classification. Comput Netw 132(Feb. 26):81–98CrossRef

21.

Yu Y, Pan Z, Hu G et al (2017) Graph classification based on sparse graph feature selection and extreme learning machine. Neurocomputing 261:20–27CrossRef

22.

Fu Q, Jing B, He P et al (2018) Fault feature selection and diagnosis of rolling bearings based on EEMD and optimized Elman_AdaBoost algorithm. IEEE Sens J 18(99):5024–5034CrossRef

23.

Lu W, Li Z, Chu J (2017) A novel computer-aided diagnosis system for breast MRI based on feature selection and ensemble learning. Comput Biol Med 83:157–165CrossRef

24.

Luan C, Dong G (2017) Experimental identification of hard data sets for classification and feature selection methods with insights on method selection. Data Knowl Eng 118:41–51CrossRef

25.

Du X, Meng C, Liu M (2019) Feature selection method based on single feature classification accuracy. J Nanjing For Univ (Nat Sci Ed) 43(04):109–116

26.

Sheikhpour R, Sarram MA, Gharaghani S et al (2017) Feature selection based on graph Laplacian by using compounds with known and unknown activities. J Chemom 31(10):e2899CrossRef

27.

Chang X, Ma Z, Lin M et al (2017) Feature interaction augmented sparse learning for fast kinect motion detection. IEEE Trans Image Process 26:3911–3920MathSciNetCrossRefMATH

28.

Chang X et al (2016) Bi-level semantic representation analysis for multimedia event detection. IEEE Trans Cybern 47:1–18

29.

Chang X, Yang Y (2016) Semisupervised feature analysis by mining correlations among multiple tasks. IEEE Trans Neural Netw Learn Syst 28:1–12MathSciNet

Title: Construction of cascaded depth model based on boosting feature selection and classification
Authors: Hongwen Yan
Zhenyu Liu
Qingliang Cui
Publication date: 30-04-2020
Publisher: Springer Berlin Heidelberg
Published in: Evolutionary Intelligence / Issue 4/2022
Print ISSN: 1864-5909
Electronic ISSN: 1864-5917
DOI: https://doi.org/10.1007/s12065-020-00413-9

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Other articles of this Issue 4/2022

Research on effective jamming style of projectile-carried communication for FH communication radio under common modulation systems

Seeking a balance between population diversity and premature convergence for real-coded genetic algorithms with crossover operator

Prediction of rock mass rating using neural network with an improved rider optimization algorithm

The analysis and research of STEAM education based on the TAM algorithm model to improve the learning effectiveness of higher vocational engineering students

Multiobjective memetic algorithm based on adaptive local search chains for vehicle routing problem with time windows

Design of distributed temperature-measuring system based on 1-wire bus for ultra-kilometre frozen deep well

Premium Partner