CREDIT CARD FRAUD DETECTION USING LINEAR DISCRIMINANT ANALYSIS (LDA), RANDOM FOREST, AND BINARY LOGISTIC REGRESSION by Muhammad Ahsan, Tabita Yuni Susanto, Tiza Ayu Virania, Andi Indra Jaya

“…In this research, we describe fraud detection as a classification issue by comparing three methods. The method used is Linear Discriminant Analysis (LDA), Random Forest, and Binary Logistic Regression. …”
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Modeling of Incident Status Dengue Fever in East Nusa Tenggara Using Geographically Weighted Logistic Regression Approach by A Meylin, N. A. Aprilianti, D Lestari, Nur Chamidah

“…A the statistical method that can be used to analyze spatial data in the form of a logistic regression equation that has a binary response variable is the Geographically Weighted Logistic Regression (GWLR) method. …”
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Multicenter Study Examining Temporal Trends in Traumatic Intracranial Hemorrhage Over Six Years Using Joinpoint Regression by Timbre Backen, Kristin Salottolo, David Acuna, Carlos H. Palacio, Gina Berg, Andrea Tsoris, Robert Madayag, Kaysie Banton, David Bar-Or

“…Patients with tICH (subdural, epidural, subarachnoid, and intracerebral hemorrhage) were identified by 10th revision of the International Statistical Classification of Diseases diagnosis codes. Temporal trends were examined over 12 six-month intervals using joinpoint regression and reported as biannual percent change (BPC); models without joinpoints are described as linear trends over time. …”
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Modelling the Trend of Zagros Forest Degradation using Logistic Regression (Case study: Chardavol Forest of Ilam province) by Ali Mahdavi, Somayeh Rangin, Hossein Mehdizadeh, Vahid Mirzaei Zadeh

“…Then, forest cover changes map and physiographic (slope, aspect, altitude) and human (distance to road and distance to residential areas) variables were integrated into regression logistic model. 3-Results and Discussion The results of the supervised classification in the studied area were compared and statistically analyzed for classification accuracy using general and Kappa reliability coefficients, as the images of years 1997 and 2014 had a total accuracy of 86.11 and 86.39%, respectively. …”
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Public Sentiment Analysis on the Boycott Israel Movement on Platform X Using Random Forest and Logistic Regression Algorithms by Rachmayanti Tri Agustin, Yana Cahyana, Kiki Ahmad Baihaqi, Tatang Rohana

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BAYESIAN ADDITIVE REGRESSION TREE APPLICATION FOR PREDICTING MATERNITY RECOVERY RATE OF GROUP LONG-TERM DISABILITY INSURANCE by Stevanny Budiana, Felivia Kusnadi, Robyn Irawan

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Monitoring and Forecasting Air Pollution Levels by Exploiting Satellite, Ground-Based, and Synoptic Data, Elaborated with Regression Models by Silas Michaelides, Dimitris Paronis, Adrianos Retalis, Filippos Tymvios

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Determination of the Effect of Some Properties on Egg Yield with Regression Analysis Met-hod Bagging Mars and R Application by Demet Canga, Mustafa Boğa

“…Earth (enhanced adaptive regression through hinges) and caret (classification and regression training), mda (Mixture Discriminant Analysis) packages were used in R STUDIO program to provide a stronger solution of regression problems in the created MARS and Bagging MARS algorithm. …”
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Employment of Regression-Based Decision Tools to Predict the Shear Capacity of Reinforced Concrete Beams Without Web Reinforcement by Saad Mahmood Raoof, Raed Mokhalad Radeef, Anfal Mansur Hameed, Shagea Alqawzai

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Near-field sound source localization using principal component analysis–multi-output support vector regression by Lanmei Wang, Yao Wang, Guibao Wang, Jianke Jia

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ROLE OF COMPUTED TOMOGRAPHY WITH PNEUMOGASTROGRAPHY IN DETERMINING THE REGRESSION GRADE OF LOCALLY ADVANCED GASTRIC CANCER AFTER NEOADJUVANT CHEMOTHERAPY by I. D. Amelina, A. M. Karachun, D. V. Nesterov, L. N. Shevkunov, A. S. Artemieva, S. S. Bagnenko, S. L. Trofimov

“…The tumor pathomorphological response to chemotherapy was assessed in all patients using a pathomorphological response rate system according to the classification of the Japanese Gastric Cancer Association (JGCA, 3rd English edition). …”
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Enhancing Sentiment and Emotion Classification with LSTM-Based Semi-Supervised Learning by Rochmat Husaini, Nur Heri Cahyana, Wisnalmawati Wisnalmawati, Tri Mardiana, Yuli Fauziah

“…The LSTM model was trained using labeled data and used to generate pseudo-labels for unlabeled data across three iterations. The performance of the pseudo-labels was evaluated using Random Forest, Logistic Regression, and Support Vector Machine (SVM). …”
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Multiple Classifier System for Handling Imbalanced and Overlapping Datasets on Multiclass Classification by Dessy Siahaan, Anwar Fitrianto, Khairil Anwar Notodiputro

“…The performance of classification models suffer when the dataset contains imbalanced and overlapping data. …”
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Application of Machine Learning in Fault Detection And Classification in Power Transmission Lines by Michel Evariste Tshodi, Nathanael Kasoro, Freddy Keredjim, ALbert Ntumba Nkongolo, Jean-Jacques Katshitshi Matondo, Paul Mbuyi Balowe, Laurent Kitoko

“…Six fault categories were found in the dataset: No-Fault (2365 occurrences), Line A Line B to Ground Fault (1134 occurrences), Three-Phase with Ground (1133 occurrences), Line-to-Line AB (1129 occurrences), Three-Phase (1096 occurrences) and finally Line-to-Line with Ground BC (1004 occurrences).…”
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Caesarean Section in Peru: Analysis of Trends Using the Robson Classification System. by Vilma Tapia, Ana Pilar Betran, Gustavo F Gonzales

“…Cochran-Armitage test was used to evaluate time trends in the rates of caesarean section rates and; logistic regression was used to evaluate risk for each classification.…”
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Utilising machine learning classification models for meteorological drought monitoring and analysis by Iqra Mumtaz, Rizwan Niaz, Zamama Sajid, Abdu Qaid Alameri, Zulfiqar Ali, Khaled A. Gepreel

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Significance of pyroptosis-related genes in the diagnosis and classification of diabetic kidney disease by Yixiong Huang, Xinke Yuan

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Comparative analysis of impact of classification algorithms on security and performance bug reports by Said Maryyam, Bin Faiz Rizwan, Aljaidi Mohammad, Alshammari Muteb

“…Comparative analysis reveals that two algorithms (SVM and LR) perform better in terms of precision (0.99) for performance bugs and three algorithms (SVM, ANN, and LR) perform better in terms of F1 score for security bugs as compared to other classification algorithms which are essentially due to the linear dataset and extensive number of features in the dataset.…”
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The effect of non-linear signal in classification problems using gene expression. by Benjamin J Heil, Jake Crawford, Casey S Greene

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Gas Detection and Classification Using Neural Network Based Gas Sensors by Munaf Ismail, Sri Arttini Dwi Prasetyowati

“…For this experiment, ANN is used as a liquid classification in grouping alcoholic and non-alcoholic liquids. …”
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