Search Results - (( program learning issues algorithm ) OR ( java application mining algorithm ))
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Direct approach for mining association rules from structured XML data
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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A web-based implementation of k-means algorithms
Published 2022“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Mining Sequential Patterns using I-PrefixSpan
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Citation Index Journal -
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Algorithm-program visualization model : An intergrated software visualzation to support novices' programming comprehension
Published 2015“…Taking into account from those main issues, this study introduces the new model of integrated algorithm-program visualization (ALPROV) for developing program comprehension tool. …”
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Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat
Published 2022“…There is also growing interest in modeling machine learning and deep learning algorithms that can learn from user’s data, understand and react to that individual’s affective state. …”
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Modeling a problem solving approach through computational thinking for teaching programming / Zebel Al Tareq
Published 2021“…This study aims to investigate teaching issues in solving programming problems and find the right approach to teach programming using a suitable problem solving approach method. …”
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…From the reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network
Published 2016“…First proposed algorithm is the combination of momentum algorithm with adaptive learning rate (ALR) algorithm, and second proposed algorithm is the combination of momentum algorithm with automatic learning rate selection (ALRS) algorithm. …”
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Particle swarm optimization for neural network learning enhancement
Published 2006“…Two programs have been developed; Particle Swarm Optimization Feedforward Neural Network (PSONN) and Genetic Algorithm Backpropagation Neural Network (GANN). …”
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A new domain specific scripting language for automated machine learning pipeline
Published 2019“…From the varieties of the machine learning algorithms, selecting the best model with the best configurations is a critical and complex design issue. …”
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Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak
Published 2021“…A comparison between built-in Scikit Learn Naive Bayes algorithm, and the scratch Naive Bayes algorithm is used to measure its effectiveness in terms of accuracy. …”
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Flock optimization algorithm-based deep learning model for diabetic disease detection improvement
Published 2024“…Hence, the research objective is to create an improved diabetic disease detection system using a Flock Optimization Algorithm-Based Deep Learning Model (FOADLM) feature modeling approach that leverages the PIMA Indian dataset to predict and classify diabetic disease cases. …”
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Differential evolution for neural networks learning enhancement
Published 2008“…Three programs have developed; Differential Evolution Neural Network (DENN), Genetic Algorithm Neural Network (GANN) and Particle Swarm Optimization with Neural Network (PSONN) to probe the impact of these methods on ANN learning using various datasets. …”
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