Search Results - (( cross validation learning algorithm ) OR ( java application using algorithm ))
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A case study of microarray breast cancer classification using machine learning algorithms with grid search cross validation
Published 2023“…Grid search cross validation (CV) is applied for hyperparameter tuning of the algorithms. …”
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Phylogenetic tree classification system using machine learning algorithm
Published 2015“…In addition to that, 10-fold cross-validation is also conducted in the evaluation. …”
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Final Year Project Report / IMRAD -
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Prediction of Machine Failure by Using Machine Learning Algorithm
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Final Year Project -
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Prediction of life expectancy for Asian population using machine learning ALGORITHMS / Nurul Shahira Pisal, Shuzlina Abdul-Rahman, Mastura Hanafiah and Saidatul Izyanie Kamarudin
Published 2022“…This study presents machine learning algorithms for life expectancy based on the Asian population dataset. …”
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Regression study for thyroid disease prediction Comparison of crossing-over approaches and multivariate analysis
Published 2022“…Future studies could explore the effects of cross-validation and multivariate analysis on other machine learning algorithms.…”
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RSA Encryption & Decryption using JAVA
Published 2006“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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Final Year Project -
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Provider independent cryptographic tools
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Monograph -
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Evaluation of the Transfer Learning Models in Wafer Defects Classification
Published 2022“…Transfer Learning is one of the common methods. Various algorithms under Transfer Learning had been developed for different applications. …”
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Job position prediction based on skills and experience using machine learning algorithm / Ezaryf Hamdan
Published 2024“…This paper proposes a sophisticated Job Position Prediction system utilizing Machine Learning algorithms and leveraging data from LinkedIn profiles. …”
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Thesis -
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Case Slicing Technique for Feature Selection
Published 2004“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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Suicide and self-harm prediction based on social media data using machine learning algorithms
Published 2023“…In combined with robust machine learning algorithms, social networking data may provide a potential path ahead. …”
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Poverty risk prediction based on socioeconomic factors using machine learning approach
Published 2025“…The findings indicated that the Logistic Regression outperformed the other algorithm with 99.06% using cross-validation and 98.42% using the splitting method, and with the best value of precision, recall, and F1-score. …”
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Student Project -
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Machine Learning Regression Approach for Estimating Energy Consumption of Appliances in Smart Home
Published 2024“…This paper attempts to use machine learning algorithms to estimate the energy consumption of appliances in a smart home environment. …”
Conference Paper -
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Development of a syncope classification algorithm from physiological signals acquired in tilt-table test
Published 2023“…Additionally, stratified 5-fold cross-validation was performed to evaluate the performance of proposed model. …”
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Final Year Project / Dissertation / Thesis -
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AI recommendation penetration testing tool for cross-site scripting: support vector machine algorithm
Published 2025“…The SVM algorithm, a supervised learning model, plays a crucial role in improving the efficiency of tool selection, ultimately enhancing the speed and adaptability of vulnerability detection processes. …”
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PV fault classification: Impact on accuracy performance using feature extraction in random-forest cross validation algorithm
Published 2024“…This paper introduces a Solar PV Smart Fault Diagnosis and Classification (SFDC) model that harnesses the Random Forest (RF) algorithm in conjunction with Cross-Validation (CV) and an optimized feature extraction (FE) set. …”
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Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.]
Published 2021“…This experiment used five common machine learning algorithms namely 1) Linear Regressor, 2) Decision Tree Regressor, 3) Random Forest Regressor, 4) Ridge Regressor and 5) Lasso Regressor tested on a real estate data-set of covering Kuala Lumpur District, Malaysia. 3 set of experiments was conducted based on the different feature selections and purposes The results show that the implementation of 16 variables based on Experiment 2 has given a promising effect on the model compare the other experiment, and the Random Forest Regressor by using the Split approach for training and validating data-set outperformed other algorithms compared to Cross-Validation approach. …”
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Conference or Workshop Item -
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Prediction of blood-brain barrier permeability of compounds by machine learning algorithms
Published 2024“…Since the CNS is often inaccessible to many complex procedures and performing in-vitro permeability studies for thousands of compounds can be laborious, attempts were made to predict the permeation of compounds through BBB by implementing the Machine Learning (ML) approach. In this work, using the KNIME Analytics platform, 4 predictive models were developed with 4 ML algorithms followed by a ten-fold cross-validation approach to predict the external validation set. …”
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DETECTION AND CLASSIFICATION OF BRAIN CANCER USING DEEP LEARNING
Published 2023“…The CNN architecture chosen was GoogleNet. To validate the robustness of the system, a 5-fold cross-validation approach was employed, ensuring reliable and consistent results. …”
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Final Year Project Report / IMRAD
