Random subspace-based ensemble modeling for near-infrared spectral diagnosis of colorectal cancer

Chen, Hui; Lin, Zan; Tan, Chao

doi:10.1016/j.ab.2018.12.009

Cited by 10 publications

(10 citation statements)

References 31 publications

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“…Where ζ is a slack variable, D is the penalty parameter [32]. Equation (3) can be transformed into the dual problem (4):…”

Section: Linear Programming Boosting (Lpboost)mentioning

confidence: 99%

“…Linear programming boosting (LPboost) ensemble learning algorithm is a variant of the Adaboost algorithm and belongs to the boosting family. It can obtain the best linear combination of weak classifiers through linear programming techniques, because of its better convergence and classification characteristics than adaboost, it has been widely used in various fields in recent years [28][29][30][31][32][33]. For example, Thaseen et al [30] proposed the integrated intrusion detection model based on LPboost, and the results showed that the strong classifier built via LPboost has better performance than a single model.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Liu et al [31] proposed a hybrid prediction model based on LPboost to predict the content of PM2.5 in the city, and the hybrid model has higher accuracy. Chen et al [32] applied LPboost in the medical field, and the results showed that it has a good effect in the diagnosis of colorectal cancer.…”

Section: Introductionmentioning

confidence: 99%

“…Chen et al. [32] applied LPboost in the medical field, and the results showed that it has a good effect in the diagnosis of colorectal cancer.…”

Section: Introductionmentioning

confidence: 99%

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Research on transformer fault diagnosis: Based on improved firefly algorithm optimized LPboost–classification and regression tree

Zhang

Fang

Zhang

et al. 2021

IET Generation Trans & Dist

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The information of dissolved gas in transformer oil can reflect the potential fault in oil immersed power transformer. In order to improve the accuracy of transformer fault diagnosis, a transformer fault diagnosis model based on IFA-LPboost-CART is proposed here. First, a LPboost-CART model is established. The classification and regression tree (CART) are used as the weak classifiers, and the linear programming boosting (LPboost) ensemble learning method is used to adjust the weight of each weak classifier to construct a strong classifier. Then the improved firefly algorithm (IFA) is adopted to optimize the number of CART and the maximum number of splits of CART in LPboost-CART to obtain the IFA-LPboost-CART model. The experimental results show that, compared with the existing methods, such as CART and support vector machine (SVM), the proposed IFA-LPboost-CART model has higher fault diagnosis accuracy, which can provide technical support for transformer fault diagnosis.

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“…Where ζ is a slack variable, D is the penalty parameter [32]. Equation (3) can be transformed into the dual problem (4):…”

Section: Linear Programming Boosting (Lpboost)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Chen et al. [32] applied LPboost in the medical field, and the results showed that it has a good effect in the diagnosis of colorectal cancer.…”

Section: Introductionmentioning

confidence: 99%

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Research on transformer fault diagnosis: Based on improved firefly algorithm optimized LPboost–classification and regression tree

Zhang

Fang

Zhang

et al. 2021

IET Generation Trans & Dist

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Ensemble classification and regression techniques combined with portable near infrared spectroscopy for facile and rapid detection of water adulteration in bovine raw milk

Ehsani

Dastgerdy

Yazdanpanah

et al. 2022

Journal of Chemometrics

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The objective of the present contribution is to use a portable near infrared (NIR) spectrometer (in spectral range of 900-1700 nm) as a rapid, facile, and nondestructive technique in combination with ensemble methods, for detection of water in bovine milk samples in concentration range 1% to 30% (v/v).On this matter, the pattern of the milk samples (pure and adulterated) was explored by principal component analysis (PCA). Then, random subspace discriminant ensemble (RSDE) was used for classification. The classification figures of merit for the RSDE method was evaluated in terms of sensitivity (Sen), specificity (Spe), accuracy (Acc), error rate (ER), and reliability (Rel). All the values were satisfactory for calibration, cross-validation, and prediction sets, which showed the reliability and robustness of the developed model. Furthermore, the performance of RSDE method was compared with partial least square-discriminant analysis (PLS-DA) and support vector machine (SVM) as the most common classification techniques. In overall, the RSDE classification outperformed the other tested classification methods (PLS-DA and RBF-SVM) in terms of accuracy and reliability. Finally, boosted regression tree (BRT) was used for quantifying the level of water adulterant in milk. The performance of the ensemble regression model was evaluated using regression coefficient (R 2 ) and root mean square error (RMSE). The values of R 2 and RMSE in prediction set for BRT were 0.95 and 0.58, respectively. The performance of BRT method was also compared with partial least squares regression (PLSR) which again showed outperformance in comparison with this frequent used regression technique.

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Development and validation of models for risk of death in patients with systemic lupus erythematosus admitted to the intensive care unit: a retrospective study

Li²

2023

Clin Rheumatol

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Random subspace-based ensemble modeling for near-infrared spectral diagnosis of colorectal cancer

Cited by 10 publications

References 31 publications

Research on transformer fault diagnosis: Based on improved firefly algorithm optimized LPboost–classification and regression tree

Research on transformer fault diagnosis: Based on improved firefly algorithm optimized LPboost–classification and regression tree

Ensemble classification and regression techniques combined with portable near infrared spectroscopy for facile and rapid detection of water adulteration in bovine raw milk

Development and validation of models for risk of death in patients with systemic lupus erythematosus admitted to the intensive care unit: a retrospective study

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