Descriptor: "random forest" - Searchworks@Jio Institute Digital Library Search Results

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70,201 results on '"random forest"'

1. Not seeing the wood for the trees: Influences on random forest accuracy.

Author: Hand, Chris and Fitkov-Norris, Elena
Subjects: RANDOM forest algorithms, RANDOM noise theory, WOOD, MACHINE learning, STATISTICAL sampling
Abstract: Machine learning classifiers are increasingly widely used. This research note explores how a particular widely used classifier, the Random Forest, performs when faced with samples which are imbalanced and noisy data. Both are known to affect accuracy, but if their effects are independent or not has not been explored. Based on an experiment using synthetic data generated for the study we find that the effects of noise and sample balance interact with each other; classification accuracy is worse when faced with both noisy data and sample imbalance. This has implications for the use of RF in market research, but also for how methods to address either sample imbalance or noise are assessed. [ABSTRACT FROM AUTHOR]
Published: 2024
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2. Predicting Short Time-to-Crime Guns: a Machine Learning Analysis of California Transaction Records (2010-2021).

Author: Laqueur, Hannah, Smirniotis, Colette, and McCort, Christopher
Subjects: Crime guns, Firearm transactions, Random forest, Risk prediction, Short time-to-crime, Variable importance, Humans, Firearms, California, Machine Learning, Crime, Commerce
Abstract: Gun-related crime continues to be an urgent public health and safety problem in cities across the US. A key question is: how are firearms diverted from the legal retail market into the hands of gun offenders? With close to 8 million legal firearm transaction records in California (2010-2020) linked to over 380,000 records of recovered crime guns (2010-2021), we employ supervised machine learning to predict which firearms are used in crimes shortly after purchase. Specifically, using random forest (RF) with stratified under-sampling, we predict any crime gun recovery within a year (0.2% of transactions) and violent crime gun recovery within a year (0.03% of transactions). We also identify the purchaser, firearm, and dealer characteristics most predictive of this short time-to-crime gun recovery using SHapley Additive exPlanations and mean decrease in accuracy variable importance measures. Overall, our models show good discrimination, and we are able to identify firearms at extreme risk for diversion into criminal hands. The test set AUC is 0.85 for both models. For the model predicting any recovery, a default threshold of 0.50 results in a sensitivity of 0.63 and a specificity of 0.88. Among transactions identified as extremely risky, e.g., transactions with a score of 0.98 and above, 74% (35/47 in the test data) are recovered within a year. The most important predictive features include purchaser age and caliber size. This study suggests the potential utility of transaction records combined with machine learning to identify firearms at the highest risk for diversion and criminal use soon after purchase.
Published: 2024

3. Sales forecasting of a food and beverage company using deep clustering frameworks.

Author: Mitra, Rony, Saha, Priyam, and Kumar Tiwari, Manoj
Subjects: SALES forecasting, FOOD industry, GAUSSIAN mixture models, RANDOM forest algorithms, RETAIL industry, HIERARCHICAL clustering (Cluster analysis)
Abstract: The competition among Food & Beverage companies has substantially increased in today's age of digitization. Sales forecasting is one of their main challenges. Due to space limitations, employee shortages, and rising online demand, retail sales forecasting became extremely important for Food and Beverage companies. This research analyzed the sales data of a multinational Food & Beverage Company. It proposed a framework using Gaussian Mixture Model (GMM) clustering, Hierarchical Agglomerative Clustering (HAC), and Random Forest algorithm for forecasting sales. This model analyzes the impact of the weekends, holidays, promotional activities, customer sentiments, festivals, and socio-economic situations in sales data and is able to forecast sales ranging from one to 15 months. An investigation of the suggested model's performance compared to numerous cutting-edge sales forecasting techniques is carried out to show its efficacy. Here, we demonstrate that the proposed hybrid model surpasses current predicting and computing efficiency methods. The results of this study can help retail managers to allocate resources and manage inventories in well-informed ways. The findings suggest that combining many strategies may produce the most precise forecasts. [ABSTRACT FROM AUTHOR]
Published: 2024
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4. Machine Learning Identification of Modifiable Predictors of Patient Outcomes After Transcatheter Aortic Valve Replacement.

Author: Russo, Mark, Elmariah, Sammy, Kaneko, Tsuyoshi, Daniels, David, Makkar, Rajendra, Chikermane, Soumya, Thompson, Christin, Benuzillo, Jose, Clancy, Seth, Pawlikowski, Amber, Lawrence, Skye, and Luck, Jeff
Subjects: TAVR, artificial intelligence, cardiology, care process, patient-centered, random forest
Abstract: BACKGROUND: Transcatheter aortic valve replacement (TAVR) is an important treatment option for patients with severe symptomatic aortic stenosis. It is important to identify predictors of excellent outcomes (good clinical outcomes, more time spent at home) after TAVR that are potentially amenable to improvement. OBJECTIVES: The purpose of the study was to use machine learning to identify potentially modifiable predictors of clinically relevant patient-centered outcomes after TAVR. METHODS: We used data from 8,332 TAVR cases (January 2016-December 2021) from 21 hospitals to train random forest models with 57 patient characteristics (demographics, comorbidities, surgical risk score, lab values, health status scores) and care process parameters to predict the end point, a composite of parameters that designated an excellent outcome and included no major complications (in-hospital or at 30 days), post-TAVR length of stay of 1 day or less, discharge to home, no readmission, and alive at 30 days. We used recursive feature elimination with cross-validation and Shapley Additive Explanation feature importance to identify parameters with the highest predictive values. RESULTS: The final random forest model retained 29 predictors (15 patient characteristics and 14 care process components); the area under the curve, sensitivity, and specificity were 0.77, 0.67, and 0.73, respectively. Four potentially modifiable predictors with relatively high Shapley Additive Explanation values were identified: type of anesthesia, direct movement to stepdown unit post-TAVR, time between catheterization and TAVR, and preprocedural length of stay. CONCLUSIONS: This study identified four potentially modifiable predictors of excellent outcome after TAVR, suggesting that machine learning combined with hospital-level data can inform modifiable components of care, which could support better delivery of care for patients undergoing TAVR.
Published: 2024

5. Microbiome-based classification models for fresh produce safety and quality evaluation.

Author: Liao, Chao, Wang, Luxin, and Quon, Gerald
Subjects: amplicon sequence variant, k-mer hash, machine learning, produce quality, produce safety, random forest, Algorithms, Microbiota, Machine Learning
Abstract: UNLABELLED: Small sample sizes and loss of sequencing reads during the microbiome data preprocessing can limit the statistical power of differentiating fresh produce phenotypes and prevent the detection of important bacterial species associated with produce contamination or quality reduction. Here, we explored a machine learning-based k-mer hash analysis strategy to identify DNA signatures predictive of produce safety (PS) and produce quality (PQ) and compared it against the amplicon sequence variant (ASV) strategy that uses a typical denoising step and ASV-based taxonomy strategy. Random forest-based classifiers for PS and PQ using 7-mer hash data sets had significantly higher classification accuracy than those using the ASV data sets. We also demonstrated that the proposed combination of integrating multiple data sets and leveraging a 7-mer hash strategy leads to better classification performance for PS and PQ compared to the ASV method but presents lower PS classification accuracy compared to the feature-selected ASV-based taxonomy strategy. Due to the current limitation of generating taxonomy using the 7-mer hash strategy, the ASV-based taxonomy strategy with remarkably less computing time and memory usage is more efficient for PS and PQ classification and applicable for important taxa identification. Results generated from this study lay the foundation for future studies that wish and need to incorporate and/or compare different microbiome sequencing data sets for the application of machine learning in the area of microbial safety and quality of food. IMPORTANCE: Identification of generalizable indicators for produce safety (PS) and produce quality (PQ) improves the detection of produce contamination and quality decline. However, effective sequencing read loss during microbiome data preprocessing and the limited sample size of individual studies restrain statistical power to identify important features contributing to differentiating PS and PQ phenotypes. We applied machine learning-based models using individual and integrated k-mer hash and amplicon sequence variant (ASV) data sets for PS and PQ classification and evaluated their classification performance and found that random forest (RF)-based models using integrated 7-mer hash data sets achieved significantly higher PS and PQ classification accuracy. Due to the limitation of taxonomic analysis for the 7-mer hash, we also developed RF-based models using feature-selected ASV-based taxonomic data sets, which performed better PS classification than those using the integrated 7-mer hash data set. The RF feature selection method identified 480 PS indicators and 263 PQ indicators with a positive contribution to the PS and PQ classification.
Published: 2024

6. A Review on Ensemble Techniques and Its Application on Social Bot Detection

Author: Sharma, Jwala, Borah, Samarjeet, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Dhar, Sourav, editor, Do, Dinh-Thuan, editor, Sur, Samarendra Nath, editor, and Imoize, Agbotiname Lucky, editor
Published: 2025
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7. Research on Real-Time Traffic Risk Warning Method Based on Random Forest and Matter-Element Model

Author: Bai, Yun, Meng, Weiheng, Gong, Yuxuan, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Lu, Xinzheng, Series Editor, Meng, Lingyun, editor, Qian, Yongsheng, editor, Bai, Yun, editor, Lv, Bin, editor, and Tang, Yuanjie, editor
Published: 2025
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8. New Approach to Support the Breast Cancer Diagnosis Process Using Frequent Pattern Growth and Stacking Based on Machine Learning Techniques

Author: Sanmartín, John, Azuero, Paulina, Hurtado, Remigio, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Julian, Vicente, editor, Camacho, David, editor, Yin, Hujun, editor, Alberola, Juan M., editor, Nogueira, Vitor Beires, editor, Novais, Paulo, editor, and Tallón-Ballesteros, Antonio, editor
Published: 2025
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9. Estimating MPdist with SAX and Machine Learning

Author: Tsoukalos, Mihalis, Chronis, Pantelis, Platis, Nikos, Vassilakis, Costas, Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Tekli, Joe, editor, Gamper, Johann, editor, Chbeir, Richard, editor, Manolopoulos, Yannis, editor, Sassi, Salma, editor, Ivanovic, Mirjana, editor, Vargas-Solar, Genoveva, editor, and Zumpano, Ester, editor
Published: 2025
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10. Predicting Next Phases of Multi-Stage Network Attacks: A Comparative Study of Statistical and Deep-Learning Models

Author: Severín, Antonia, Canales, Claudio, Torres, Romina, Roudergue, César, Salas, Rodrigo, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Hernández-García, Ruber, editor, Barrientos, Ricardo J., editor, and Velastin, Sergio A., editor
Published: 2025
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11. A Comparative Study of MNL and Machine Learning Methods for Travel Mode Choice of Medical Travel

Author: Huang, Pengpeng, Gong, Lei, Lei, Tian, Wang, Jia, Zhu, Cheng, Zhang, Zheng, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Lu, Xinzheng, Series Editor, Meng, Lingyun, editor, Qian, Yongsheng, editor, Bai, Yun, editor, Lv, Bin, editor, and Tang, Yuanjie, editor
Published: 2025
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12. Prediction of Compaction Parameters Based on the Atterberg Limit by Using a Machine Learning Approach

Author: Kassa, Semachew Molla, Wubineh, Betelhem Zewdu, Geremew, Africa Mulumar, Azmatch, Tezera Firew, Kumar, Nandyala Darga, Chlamtac, Imrich, Series Editor, Birhane, Abeba, editor, Shewarega, Fekadu, editor, Bitew, Mekuanint A., editor, Wagaw, Mekonnen, editor, and Abebe Ashetehe, Ahunim, editor
Published: 2025
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13. A Survey on Datasets, Feature Extraction and Classification Techniques Used in Personality Classification from Handwriting

Author: Garg, Parul, Garg, Naresh Kumar, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Khurana, Meenu, editor, Thakur, Abhishek, editor, Kantha, Praveen, editor, Shieh, Chin-Shiuh, editor, and Shukla, Rajesh K., editor
Published: 2025
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14. Random Forest Model Parameters Optimization

Author: Tran, Thuy Thi, Phan, Nghia Quoc, Huynh, Hiep Xuan, Li, Gang, Series Editor, Filipe, Joaquim, Series Editor, Ghosh, Ashish, Series Editor, Xu, Zhiwei, Series Editor, Thai-Nghe, Nguyen, editor, Do, Thanh-Nghi, editor, and Benferhat, Salem, editor
Published: 2025
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15. Prediction of Rainfall in One of the Wettest Regions in India Using Machine Learning Methods

Author: Singh, Vishal, Singh, Japjeet, Jain, Sanjay Kumar, Singh, Pushpendra Kumar, Marques, Oge, Series Editor, Chaudhury, Baishali, Editorial Board Member, Culibrk, Dubravko, Editorial Board Member, Hadid, Abdenour, Editorial Board Member, Kitamura, Felipe, Editorial Board Member, Riegler, Michael, Editorial Board Member, Schumacher, Joe, Editorial Board Member, Soares, Anderson, Editorial Board Member, Stojanovic, Branka, Editorial Board Member, Thampi, Sabu, Editorial Board Member, Van Ooijen, Peter, Editorial Board Member, Willingham, David, Editorial Board Member, Srivastav, Roshan, and Nayak, Purna C.
Published: 2025
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16. Graph Neural Network-Based Malicious Node Detection to Improve the Security of Wireless Sensor Networks

Author: Kumar, K., Khari, M., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Goar, Vishal, editor, Kuri, Manoj, editor, Kumar, Rajesh, editor, and Senjyu, Tomonobu, editor
Published: 2025
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17. Fusion of Deep and Local Features Using Random Forests for Neonatal HIE Segmentation

Author: Eddine Toubal, Imad, Soltani Kazemi, Elham, Rahmon, Gani, Kucukpinar, Taci, Almansour, Mohamed, Ho, Mai-Lan, Palaniappan, Kannappan, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Bao, Rina, editor, Grant, Ellen, editor, Kirkpatrick, Andrew, editor, Wachs, Juan, editor, and Ou, Yangming, editor
Published: 2025
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18. Revolutionizing Road Safety: Machine Learning Approaches for Predicting Road Accident Severity

Author: Malik, Meenakshi, Nandal, Rainu, Chhikara, Rita, Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Bairwa, Amit Kumar, editor, Tiwari, Varun, editor, Vishwakarma, Santosh Kumar, editor, Tuba, Milan, editor, and Ganokratanaa, Thittaporn, editor
Published: 2025
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19. Aggressive Bangla Text Detection Using Machine Learning and Deep Learning Algorithms

Author: Rosni, Tanjela Rahman, Hasan, Mahamudul, Mittra, Tanni, Ali, Md. Sawkat, Ferdaus, Md. Hasanul, Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Bairwa, Amit Kumar, editor, Tiwari, Varun, editor, Vishwakarma, Santosh Kumar, editor, Tuba, Milan, editor, and Ganokratanaa, Thittaporn, editor
Published: 2025
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20. Empirical Validation of Software Defect Prediction Models Using Grid Search Gray Wolf Optimization

Author: Malhotra, Ruchika, Meena, Shweta, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Fortino, Giancarlo, editor, Kumar, Akshi, editor, Swaroop, Abhishek, editor, and Shukla, Pancham, editor
Published: 2025
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21. An Ensemble-Based Approach for Smart Detection of Heart Diseases Symptoms

Author: Balaji, Prasanalakshmi, Bansal, Shivam, Banerjee, Subham, Mishra, Sushruta, Sridevi, R., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Fortino, Giancarlo, editor, Kumar, Akshi, editor, Swaroop, Abhishek, editor, and Shukla, Pancham, editor
Published: 2025
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22. Sentiment Analysis of Amazon Alexa Product Reviews: A Comprehensive Comparative Study of Learning Algorithms

Author: Rao, Gouravelli Akshith, Prakash, L. N. C. K., Suryanarayana, G., Joshua, Pathi Varun, Reddy, Katta Nithin Kumar, Karnati, Ramesh, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Kumar, Amit, editor, Gunjan, Vinit Kumar, editor, Senatore, Sabrina, editor, and Hu, Yu-Chen, editor
Published: 2025
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23. An Effective Prediction of Heart Diseases Using Machine Learning Techniques

Author: Obulesu, O., Yakshitha, Koulampeta, Vuyyuru, Sanjana, Meenakshi, Tumkur, Vaishnavi, Pujala, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Kumar, Amit, editor, Gunjan, Vinit Kumar, editor, Senatore, Sabrina, editor, and Hu, Yu-Chen, editor
Published: 2025
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24. Anomaly Detection Within Mission-Critical Call Processing

Author: Doris, Sean, Salem, Iosif, Schmid, Stefan, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Masuzawa, Toshimitsu, editor, Katayama, Yoshiaki, editor, Kakugawa, Hirotsugu, editor, Nakamura, Junya, editor, and Kim, Yonghwan, editor
Published: 2025
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25. Enhancing IoT Network Defense: A Comparative Study of Machine Learning Algorithms for Attack Classification

Author: McNair, Alkendria, Precious-Esue, Divine, Newson, Soundra, Rahimi, Nick, Ghosh, Ashish, Editorial Board Member, Feng, Wenying, editor, Rahimi, Nick, editor, and Margapuri, Venkatasivakumar, editor
Published: 2025
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26. Artificial Intelligence-Based Quantification and Prognostic Assessment of CD3, CD8, CD146, and PDGF-Rβ Biomarkers in Sporadic Colorectal Cancer

Author: Lohmann, Florencia Adriana, Specterman Zabala, Martín Isac, Soarez, Julieta Natalia, Dádamo, Maximiliano, Loresi, Mónica Alejandra, de las Nieves Diaz, María, Pavicic, Walter Hernán, Bolontrade, Marcela Fabiana, Risk, Marcelo Raúl, Santino, Juan Pablo, Vaccaro, Carlos Alberto, Piñero, Tamara Alejandra, Ghosh, Ashish, Editorial Board Member, Florez, Hector, editor, and Astudillo, Hernán, editor
Published: 2025
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27. Extracting Daily Aggregate Load Profiles from Monthly Consumption

Author: Saraf, Anmol, Kowli, Anupama, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Jørgensen, Bo Nørregaard, editor, Ma, Zheng Grace, editor, Wijaya, Fransisco Danang, editor, Irnawan, Roni, editor, and Sarjiya, Sarjiya, editor
Published: 2025
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28. A Machine Learning-Based Marine Vessel/Ship Classification Using Passive Sonar Signals—A Multi-class Problem

Author: Malkapurapu, Sai Kiran, Guntupalli, Venkat, Manapaka, Bhanu Nivas, Thadikemalla, Venkata Sainath Gupta, Howlett, Robert J., Series Editor, Jain, Lakhmi C., Series Editor, Pal, Sankar K., editor, Thampi, Sabu M., editor, and Abraham, Ajith, editor
Published: 2025
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29. Rainfall Forecasting Using High Spatiotemporal Satellite Imagery and Machine Learning Techniques: A Case Study Using INSAT 3DR Data

Author: Deepthi Sasidhar, V., Anuradha, T., Ajay Kumar, M. V., Howlett, Robert J., Series Editor, Jain, Lakhmi C., Series Editor, Pal, Sankar K., editor, Thampi, Sabu M., editor, and Abraham, Ajith, editor
Published: 2025
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30. Detecting Faulty Steel Plates Using Machine Learning

Author: Dorbane, Abdelhakim, Harrou, Fouzi, Sun, Ying, Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Singh, Mayank, editor, Tyagi, Vipin, editor, Gupta, P. K., editor, Flusser, Jan, editor, Ören, Tuncer, editor, Cherif, Amar Ramdane, editor, and Tomar, Ravi, editor
Published: 2025
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31. Machine Learning-Based Approach to Predict Heart Diseases Using Fused Dataset

Author: Uddin, Khandaker Mohammad Mohi, Mohamed, Abdirahman, Biswas, Nitish, Mostafiz, Rafid, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Mahmud, Mufti, editor, Kaiser, M. Shamim, editor, Bandyopadhyay, Anirban, editor, Ray, Kanad, editor, and Al Mamun, Shamim, editor
Published: 2025
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32. Stock Open Price Prediction of Software Companies in the BSE SENSEX 50 Index

Author: Sonar, Chhaya, Al Hammadi, Ahmed M., Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Weber, Gerhard-Wilhelm, editor, Martinez Trinidad, Jose Francisco, editor, Sheng, Michael, editor, Ramachand, Raghavendra, editor, Kharb, Latika, editor, and Chahal, Deepak, editor
Published: 2025
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33. Advancing Precision Agriculture: Machine Learning-Based Crop Recommendation for Optimal Yield

Author: Bouni, Mohamed, Hssina, Badr, Douzi, Khadija, Douzi, Samira, Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Weber, Gerhard-Wilhelm, editor, Martinez Trinidad, Jose Francisco, editor, Sheng, Michael, editor, Ramachand, Raghavendra, editor, Kharb, Latika, editor, and Chahal, Deepak, editor
Published: 2025
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34. Sells Sprint: Leveraging Machine-Learning Techniques for Ensuring Trust in Online Marketplaces

Author: Kumar, Manni, Ali, Md, Molla, Basten Ahamad, Srivastava, Khushi, De, Manish, Verma, Aman, Das, Swagatam, Series Editor, Bansal, Jagdish Chand, Series Editor, Jaiswal, Ajay, editor, Anand, Sameer, editor, Hassanien, Aboul Ella, editor, and Azar, Ahmad Taher, editor
Published: 2025
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35. SARF: Stock Market Prediction with Sentiment-Augmented Random Forest

Author: Talazadeh, Saber, Peraković, Dragan, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin, Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Perakovic, Dragan, editor, and Knapcikova, Lucia, editor
Published: 2025
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36. Customer Churn Rate Prediction Using Machine Learning Techniques for E-Commerce Sector

Author: Saxena, Muskan, Aggarwal, Nikita, Gupta, Rekha, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Hassanien, Aboul Ella, editor, Anand, Sameer, editor, Jaiswal, Ajay, editor, and Kumar, Prabhat, editor
Published: 2025
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37. Machine Learning for the Identification of Biomarker and Risk Factors associated with Depression in Adult Population: Preliminary Results on a Small Cohort

Author: Cano-Escalera, Guillermo, Graa, Manuel, MacDowell, Karina S., Leza, Juan C., Zorilla, Iaki, Gonzlez-Pinto, Ana, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Quintián, Héctor, editor, Corchado, Emilio, editor, Troncoso Lora, Alicia, editor, Pérez García, Hilde, editor, Jove Pérez, Esteban, editor, Calvo Rolle, José Luis, editor, Martínez de Pisón, Francisco Javier, editor, García Bringas, Pablo, editor, Martínez Álvarez, Francisco, editor, Herrero, Álvaro, editor, and Fosci, Paolo, editor
Published: 2025
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38. Enhancing Hate Speech Detection: Evaluation of Classification Models and Techniques

Author: Dodda, Ratnam, Putta, Pooja Reddy, Shulamite, Elthuri Chelsi, Ashwini, Kalmuri, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Kumar, Amit, editor, Gunjan, Vinit Kumar, editor, Senatore, Sabrina, editor, and Hu, Yu-Chen, editor
Published: 2025
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39. Predicting the Need for Mental Treatment Across Various Age Groups Using Machine Learning Algorithm

Author: Pal, Surya Kant, Rawat, Himani, Roy, Rita, Khan, Ameer Lareb, Kumari, Nisha, Srivastava, Prashasya, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Kumar, Amit, editor, Gunjan, Vinit Kumar, editor, Senatore, Sabrina, editor, and Hu, Yu-Chen, editor
Published: 2025
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40. Forecasting Pupils Performance through Machine Learning Approaches

Author: Raj, Amara Rithik, Regulwar, Ganesh B., Anvitha, Rangineni, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Kumar, Amit, editor, Gunjan, Vinit Kumar, editor, Senatore, Sabrina, editor, and Hu, Yu-Chen, editor
Published: 2025
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41. Accident Severity Detection Using Machine Learning Algorithms

Author: Kumar, B. Naveen, Kumar, N. Sunil, Kumar, U. Naresh, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Kumar, Amit, editor, Gunjan, Vinit Kumar, editor, Senatore, Sabrina, editor, and Hu, Yu-Chen, editor
Published: 2025
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42. Software Fault Prediction Using ML Algorithms

Author: Neha, T., Anusha, M., Anusha, D., Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Kumar, Amit, editor, Gunjan, Vinit Kumar, editor, Senatore, Sabrina, editor, and Hu, Yu-Chen, editor
Published: 2025
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43. Comparative Analysis of Classifiers for Chat Classification: A Study on Random Forest, Support Vector Machine, and Multinomial Naive Bayes with Bag of Words and TF-IDF

Author: Hemakirthiga, K., Arunadevi, J., Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Geetha, R., editor, Dao, Nhu-Ngoc, editor, and Khalid, Saeed, editor
Published: 2025
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44. Detection and Classification of Intracranial Tumor in Machine Learning Using Fuzzy C-Means Algorithm

Author: Roobika, R., Shanthi, D., Sivakamy, N., Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Geetha, R., editor, Dao, Nhu-Ngoc, editor, and Khalid, Saeed, editor
Published: 2025
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45. Optimizing Coronary Illness Prediction Using Hyperparameter Tuning Through Machine Learning

Author: Vaishnavi, M. G., Shanthi, D., Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Geetha, R., editor, Dao, Nhu-Ngoc, editor, and Khalid, Saeed, editor
Published: 2025
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46. Ensemble Learning-Based Android Malware Detection

Author: Priya, V., Sathya Sofia, A., Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Geetha, R., editor, Dao, Nhu-Ngoc, editor, and Khalid, Saeed, editor
Published: 2025
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47. A Comparative Evaluation of Machine Learning Methods for Predicting Chronic Kidney Disease

Author: Navaz, K., Yazhinian, S., Pillai, N. Muthuvairavan, Purushotham, N., Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Geetha, R., editor, Dao, Nhu-Ngoc, editor, and Khalid, Saeed, editor
Published: 2025
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48. Diagnosis of Parkinson’s Disease Using Machine Learning and Deep Learning Techniques

Author: Sharanyaa, S., Sambath, M., Ganesh, A., Ahmed, A. Hammadh, Ganesh, S., Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Geetha, R., editor, Dao, Nhu-Ngoc, editor, and Khalid, Saeed, editor
Published: 2025
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49. Prediction of Rutting Depth Using Random Forest Methods in Full-Depth Reclamation Asphalt Pavements

Author: Evers, Eli, Shrestha, Atithi, Garcia, Erick, Cho, Haechad, Bashar, Mohammad Z., Torres-Machi, Cristina, Choi, Kunhee, Yeo, Hwasoo, Zhang, Yunlong, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Lu, Xinzheng, Series Editor, Desjardins, Serge, editor, Poitras, Gérard J., editor, and Nik-Bakht, Mazdak, editor
Published: 2025
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50. Machine Learning Algorithms

Author: Gupta, Pramod, Sehgal, Naresh Kumar, Acken, John M., Gupta, Pramod, Sehgal, Naresh Kumar, and Acken, John M.
Published: 2025
Full Text: View/download PDF

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