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Integrating machine learning and multi-omics analysis to unveil key programmed cell death patterns and immunotherapy targets in kidney renal clear cell carcinoma
Published 2025-05-01“…We utilized a combination of 101 machine learning algorithms to analyze the TCGA-KIRC cohort and the GSE22541 KIRC patients, screening for cell death patterns closely associated with prognosis from 18 potential modes. …”
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Fine-Pruning: A biologically inspired algorithm for personalization of machine learning models
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Forecasting household monthly electricity consumption using the similar pattern algorithm
Published 2025-02-01“… This article discusses forecasting the monthly electricity consumption time series of household subscribers using the similar pattern algorithm, which uses each subscriber’s unique consumption pattern. …”
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Comparison of the Performance of the C.45 Algorithm with Naive Bayes in Analyzing Book Borrowing at the Library Pringsewu Muhammadiyah University
Published 2025-01-01“…This study examines the effectiveness of the Naïve Bayes and C4.5 algorithms in analyzing book borrowing patterns at the Pringsewu Muhammadiyah University Library. …”
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Numerical Optimization of Polygon Tessellation for Generating Machine-producible Crochet Patterns
Published 2023-10-01“…Generally speaking, the algorithm extends the toolbox for designing machine-crocheted fabrics through the automated generation of valid crochet patterns corresponding to input shapes and according to the possibilities of the CroMat crocheting machine prototype. …”
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Stock Price Pattern Prediction Based on Complex Network and Machine Learning
Published 2019-01-01“…Next, the topology characteristic variables for each combination symbolic pattern are used as the input variables for K-nearest neighbors (KNN) and support vector machine (SVM) algorithms to predict the next-day volatility patterns of a single stock. …”
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Support Vector Machines and Model Selection for Control Chart Pattern Recognition
Published 2025-02-01“…To conquer these downsides, algorithms for control chart pattern recognition (CCPR) leverage machine learning models to detect non-normality or normality and ensure product quality is established, and novel approaches that integrate the support vector machine (SVM), random forest (RF), and K-nearest neighbors (KNN) methods with the model selection criterion, named SVM-, RF-, and KNN-CCPR, respectively, are proposed. …”
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Algorithmically Enhanced Wearable Multimodal Emotion Sensor
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APPLYING SOME MATCHING ALGORITHMS FOR SEQUENCE IGNATURE TO ANALYZE AND DETECT ENTRIES INTO SYSTEM NETWORKS
Published 2013-06-01“…Additionally, tools for network monitoring such as open source munintools,are also used to analyze and evaluate the performance of network-attack. Next, the time of pattern identification in the Snort's machine, and the performance of Snort as well as the number of packets passing through Snort, the amount of alerts per second, connection speed in real time, the percentage of received data in pattern matching process, etc. are also measured based on intelligent algorithms built in Snort. …”
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Spatiotemporal Mapping of Grazing Livestock Behaviours Using Machine Learning Algorithms
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Four Machine Learning Algorithms for Biometrics Fusion: A Comparative Study
Published 2012-01-01“…We examine the efficiency of four machine learning algorithms for the fusion of several biometrics modalities to create a multimodal biometrics security system. …”
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PREDICTION OF TELECOM SERVICES CONSUMERS CHURN BY USING MACHINE LEARNING ALGORITHMS
Published 2022-11-01“…The name "machine learning" refers to the automated detection of meaningful patterns in large data sets. …”
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PREDICTION OF TELECOM SERVICES CONSUMERS CHURN BY USING MACHINE LEARNING ALGORITHMS
Published 2022-11-01“…The name "machine learning" refers to the automated detection of meaningful patterns in large data sets. …”
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Advanced Methodology for Fraud Detection in Energy Using Machine Learning Algorithms
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Predicting agricultural drought in central Europe by using machine learning algorithms
Published 2025-04-01“…Thus, this research evaluates the patterns and magnitude of agriculture droughts using Standardized Precipitation Evapotranspiration Index (SPEI) from 1926 to 2020 in eastern Hungary, and assess the performance of six machine learning models (Random Forest (RF), Extra Trees (ET), Gradient Boosting (GB), Extreme Gradient Boost (XGB), Support Vector Machines (SVM), and Multi-Layer Perceptron (ANN-MLP)) in predicting agriculture droughts. …”
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Purchasing Prediction Using Machine Learning Algorithms for Optimizing Inventory Management
Published 2025-03-01“…Along with technological developments, traditional methods of inventory management are starting to be replaced by data-based approaches and machine learning algorithms. The use of machine learning is not only limited to predicting purchasing needs, but can also be applied in various other business aspects. …”
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Application of machine learning algorithm to predict the behavior of stocks marketed in Brazil
Published 2025-07-01“…This work analyzes the application of machine learning algorithms in the selection of portfolios in the Brazilian market. …”
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Healthcare Prediction Using Novel Machine Learning Methods and Metaheuristic Algorithm
Published 2025-06-01“…These days, machine learning (ML) is one of the most important technologies, especially in the field of healthcare. …”
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Live Weight Prediction in Norduz Sheep Using Machine Learning Algorithms
Published 2022-04-01“…There were no differences between the means of actual and predicted LWs by machine learning models. The fact that the models generalized well on the testing data sets indicates that machine learning algorithms have valid predictive patterns and are effective methods in LW weight of Norduz sheep. …”
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