Search Results - regression ((((tree algorithm) OR (acs algorithm))) OR (new algorithm))

Extended spatial decision tree algorithm for classifying hotspot occurrence by Sitanggang, Imas Sukaesih

“…Therefore spatial objects should be included in forest fires datasets for classifying hotspots occurrence in order to obtain the classifiers with high accuracy. This work proposes a new spatial decision tree algorithm namely the extended spatial ID3 decision tree algorithm to classify hotspots occurrence from a forest fires dataset that contains point, line and polygon features. …”
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Outlier detection in circular regression model using minimum spanning tree method by Nur Faraidah, Muhammad Di, Siti Zanariah, Satari, Roslinazairimah, Zakaria

“…Therefore, this study aims to develop new algorithms that can detect outliers by using the minimum spanning tree method. …”
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A Hybrid Adaptive Leadership GWO Optimization with Category Gradient Boosting on Decision Trees Algorithm for Credit Risk Control Classification by Suihai, Chen, Chih How, Bong, Po Chan, Chiu

“…Thirdly, this study uses SHAP framework to improve the interpretability of the new algorithm (EBGWO-CatBoost), and solves the problem of the weak interpretability of the new algorithm. …”
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Integrated support vector regression and an improved particle swarm optimization-based model for solar radiation prediction by Ghazvinian H., Mousavi S.-F., Karami H., Farzin S., Ehteram M., Hossain M.S., Fai C.M., Hashim H.B., Singh V.P., Ros F.C., Ahmed A.N., Afan H.A., Lai S.H., El-Shafie A.

Outlier detection in circular regression model using minimum spanning tree method by Nur Faraidah, Muhammad Di, Siti Zanariah, Satari, Roslinazairimah, Zakaria

“…Therefore, this study aims to develop new algorithms that can detect outliers by using minimum spanning tree method. …”
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Prediction of Oil Palm Yield Using Machine Learning in the Perspective of Fluctuating Weather and Soil Moisture Conditions: Evaluation of a Generic Workflow by Khan N., Kamaruddin M.A., Ullah Sheikh U., Zawawi M.H., Yusup Y., Bakht M.P., Mohamed Noor N.

“…The prediction was followed by data preprocessing and feature selection. Selected regression models were compared with Random Forest, Gradient Boosting, Decision Tree, and other non-tree algorithms to prove the R2 driven performance superiority of tree-based ensemble models. …”

Detection of multiple outliners in linear regression using nonparametric methods by Adnan, Robiah

“…REFERENCES Agullo, J. (2000). New Algorithms for Computing the Least Trimmed Squares Regression Estimator. …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

“…Lastly, we consider the problem of detecting multiple outliers in circular regression models based on the clustering algorithm. …”
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Prediction of stroke disease using machine learning techniques / Syarifah Adilah Mohamed Yusoff ... [et al.] by Mohamed Yusoff, Syarifah Adilah, Warris, Saiful Nizam, Abu Bakar, Mohd Saifulnizam, Kadar, Rozita

“…The five models were Decision Tree, Logistic Regression, Linear Discriminant Analysis, Gaussian Naïve Bayes and Support Vector Machine, have being implemented to predict binary outcome of stroke and no stroke. …”
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A New Machine Learning-based Hybrid Intrusion Detection System and Intelligent Routing Algorithm for MPLS Network by Ridwan M.A., Radzi N.A.M., Azmi K.H.M., Abdullah F., Ahmad W.S.H.M.W.

Machine learning algorithms on price and rent predictions in real estate: A systematic literature review / Muhamad Harussani Abdul Salam ... [et al.] by Abdul Salam, Muhamad Harussani, Mohd, Thuraiya, Masrom, Suraya, Johari, Noraini, Mohamad Saraf, Mohamad Haizam

“…This study will provide new insights on the Machine Learning Algorithms in the real estate industry.…”
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Two steps hybrid calibration algorithm of support vector regression and K-nearest neighbors by Hamed, Y., Ibrahim Alzahrani, A., Shafie, A., Mustaffa, Z., Che Ismail, M., Kok Eng, K.

“…On the other hand, non-parametric calibration models can overcome the normality limitation, however, they provide only a local or general estimation. This paper presents a new hybrid calibration model that is based on two steps K nearest neighbor interpolation and support vector regression. …”
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Loan eligibility classification using logistic regression by Lik Pao, Paul Law, Mohd Arfian, Ismail

“…Machine learning is becoming increasingly vital in various domains, including loan eligibility classification, d ue to its ability to analyze large amounts of data, develop predictive models, adapt to new information, and automate processes. This research paper presents a study on loan eligibility classification using a machine learning approach by comparing the performance of three Machine Learning algorithms which were Logistic Regression, Random Forest, and Decision Tree. …”
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Loan Eligibility Classification Using Machine Learning Approach by Law, Paul Lik Pao

“…Machine learning is becoming increasingly vital in various domains, including loan eligibility classification, due to its ability to analyze large amounts of data, develop predictive models, adapt to new information, and automate processes. This research paper presents a study on loan eligibility classification using a machine learning approach by comparing the performance of three Machine Learning algorithms which were Logistic Regression, Random Forest, and Decision Tree. …”
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Predictive models for hotspots occurrence using decision tree algorithms and logistic regression. by Sitanggang, Imas Sukaesih, Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin

“…Furthermore, the logistic regression model outperforms the decision tree algorithms with the accuracy of 68.63%. …”
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Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data by Oyebayo, Olaniran Ridwan

“…BRF algorithm combines the strengths of random subset and greedy selection procedures in creating new maximal ordered variable relevance weights. …”
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AnkPlex: algorithmic structure for refinement of near-native ankyrin-protein docking by Wisitponchai, Tanchanok, Shoombuatong, Watshara, Lee, Vannajan Sanghiran, Kitidee, Kuntida, Tayapiwatana, Chatchai

“…Subsequently, a re-scoring rank was generated by AnkPlex using a combination of a decision tree algorithm and logistic regression. AnkPlex achieved superior efficiency with ≥1 near-native complexes in the 10 top-rankings for nine X-ray complexes compared to ZDOCK, which only obtained six X-ray complexes. …”
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Translating conventional wisdom on chicken comb color into automated monitoring of disease-infected chicken using chromaticity-based machine learning models by Bakar M.A.A.A., Ker P.J., Tang S.G.H., Baharuddin M.Z., Lee H.J., Omar A.R.

“…The development of the algorithms shows that Logistic Regression, SVM with Linear and Polynomial kernels performed the best with 95% accuracy, followed by SVM-RBF kernel, and KNN with 93% accuracy, Decision Tree with 90% accuracy, and lastly, SVM-Sigmoidal kernel with 83% accuracy. …”

Do CEO and chairman characteristics affect green innovation? evidence from a comparative analysis of machine learning models by Xue, Ruixiang, Ong, Tze San, Demir, Ezgi

“…It has been used a sample of listed companies in China from 2010 to 2022 to compare it with the gradient-boosted decision tree (GBDT) model and multiple linear regression (MLR) model. …”
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A review of deep learning and machine learning techniques for hydrological inflow forecasting by Latif S.D., Ahmed A.N.

“…In this study, we look at the long short-term memory deep learning method as well as three traditional machine learning algorithms: support vector machine, random forest, and boosted regression tree. …”