A : Extending area under the ROC curve for probabilistic labels

Rachakonda, Aditya Ramana; Bhatnagar, Ayush

doi:10.1016/j.patrec.2021.06.023

Cited by 12 publications

(5 citation statements)

References 13 publications

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“…The receiver operating characteristics (ROC) graph has the property of organizing the classifier model and visualizing its performance [35]. The ROC is usually used to measure the relative difference between the true positive rate and the false positive rate [36]. It is memorable that the true positive rate is that rate at which classifier model obtains [positive] for those observations that are truly positive, whereas the false positive rate is that rate at which classifier model obtains [positive] for those observations that are truly negative [14].…”

Section: Resultsmentioning

confidence: 99%

Neural Network-Based Classifier for Collision Classification and Identification for a 3-DOF Industrial Robot

Mahmoud,

Abdel-Jaber,

Sharkawy

2024

Automation

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In this paper, the aim is to classify torque signals that are received from a 3-DOF manipulator using a pattern recognition neural network (PR-NN). The output signals of the proposed PR-NN classifier model are classified into four indicators. The first predicts that no collisions occur. The other three indicators predict collisions on the three links of the manipulator. The input data to train the PR-NN model are the values of torque exerted by the joints. The output of the model predicts and identifies the link on which the collision occurs. In our previous work, the position data for a 3-DOF robot were used to estimate the external collision torques exerted by the joints when applying collisions on each link, based on a recurrent neural network (RNN). The estimated external torques were used to design the current PR-NN model. In this work, the PR-NN model, while training, could successfully classify 56,592 samples out of 56,619 samples. Thus, the model achieved overall effectiveness (accuracy) in classifying collisions on the robot of 99.95%, which is almost 100%. The sensitivity of the model in detecting collisions on the links “Link 1, Link 2, and Link 3” was 97.9%, 99.7%, and 99.9%, respectively. The overall effectiveness of the trained model is presented and compared with other previous entries from the literature.

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Section: Resultsmentioning

confidence: 99%

Neural Network-Based Classifier for Collision Classification and Identification for a 3-DOF Industrial Robot

Mahmoud,

Abdel-Jaber,

Sharkawy

2024

Automation

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“…In order to demonstrate the performance of classifier, the identification results are evaluated as a function of sensitivity, specificity, and F1-score. The TPR, FPR, sensitivity, specificity, and F1-score can be calculated as follows [ 53 , 54 ]:

where TP, TN, FP, and FN are the true positive, false positive, false negative, and true negative, respectively. The AUC score is the result of the integration of the ROC curve.…”

Section: Methodsmentioning

confidence: 99%

Artificial Intelligence-Assisted Terahertz Imaging for Rapid and Label-Free Identification of Efficient Light Formula in Laser Therapy

et al. 2022

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Photodynamic therapy (PDT) is considered a promising noninvasive therapeutic strategy in biomedicine, especially by utilizing low-level laser therapy (LLLT) in visible and near-infrared spectra to trigger biological responses. The major challenge of PDT in applications is the complicated and time-consuming biological methodological measurements in identification of light formulas for different diseases. Here, we demonstrate a rapid and label-free identification method based on artificial intelligence (AI)-assisted terahertz imaging for efficient light formulas in LLLT of acute lung injury (ALI). The gray histogram of terahertz images is developed as the biophysical characteristics to identify the therapeutic effect. Label-free terahertz imaging is sequentially performed using rapid super-resolution imaging reconstruction and automatic identification algorithm based on a voting classifier. The results indicate that the therapeutic effect of LLLT with different light wavelengths and irradiation times for ALI can be identified using this method with a high accuracy of 91.22% in 33 s, which is more than 400 times faster than the biological methodology and more than 200 times faster than the scanning terahertz imaging technology. It may serve as a new tool for the development and application of PDT.

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“…Area Under the Curve (AUC-ROC) adalah ukuran yang menggambarkan kinerja keseluruhan model. Ini mengukur area di bawah kurva ROC, dengan nilai maksimum 1 yang menunjukkan kinerja sempurna dan nilai 0,5 yang menunjukkan kinerja yang sama dengan pemilihan acak [23], [24].…”

Section: Metodeunclassified

Analisis Perilaku Pelanggan menggunakan Metode Ensemble Logistic Regression

Usman,

Aziz

2023

JUTIKOMP

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Customer behavior analysis is crucial for companies, especially Small and Medium Enterprises (SMEs), to make strategic decisions. Through customer behavior analysis, patterns of customer behavior in purchasing a product or service can be identified. This provides insights into preferences and the right strategies to maintain or increase customer loyalty. This research aims to analyze customer behavior using the ensemble logistic regression method. Data was collected from the company's customer database over the last 5 years. Customer behavior is characterized by gender, age, and the preferred vehicle transmission type. The ensemble logistic regression method was implemented to improve model accuracy. The results show that the ensemble technique can enhance the accuracy of the Logistic Regression method. Model accuracy significantly increased with boosting, achieving an accuracy of 76%, while the model with bagging achieved an accuracy of 75%.

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A : Extending area under the ROC curve for probabilistic labels

Cited by 12 publications

References 13 publications

Neural Network-Based Classifier for Collision Classification and Identification for a 3-DOF Industrial Robot

Neural Network-Based Classifier for Collision Classification and Identification for a 3-DOF Industrial Robot

Artificial Intelligence-Assisted Terahertz Imaging for Rapid and Label-Free Identification of Efficient Light Formula in Laser Therapy

Analisis Perilaku Pelanggan menggunakan Metode Ensemble Logistic Regression

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