Search Results - (( java implementation mining algorithm ) OR ( using learning method algorithm ))
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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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Thesis -
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Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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Thesis -
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Scalable approach for mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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Mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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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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Final Year Project / Dissertation / Thesis -
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Image clustering comparison of two color segmentation techniques
Published 2010“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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Phishing attack detection using machine learning method
Published 2019“…After a study has been made, machine learning method is used to prevent the phishing attack. …”
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Undergraduates Project Papers -
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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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Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms
Published 2021“…The objective of this study is to perform DM classification using various machine learning algorithms using Weka as a tool. …”
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Final Year Project -
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Autism Spectrum Disorder Classification Using Deep Learning
Published 2021“…Recently, deep learning methods have significantly sharpened the cutting edge of learning algorithms in a wide range of artificial intelligence tasks. …”
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Article -
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Fractional Stochastic Gradient Descent Based Learning Algorithm For Multi-layer Perceptron Neural Networks
Published 2021“…Conventionally back-propagation learning algorithm also termed as (BP-MLP) is used. …”
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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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Fast sequential learning methods on RBF-network using decomposed training algorithms
Published 2004“…This work investigates novel sequential learning methods applied on a decomposed form of training algorithms using radial basis function (RBF) network. …”
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Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method
Published 2024“…Thus, this study proposed an Opposition-based Learning Binary Bat Algorithm as the feature selection technique in the T-method. …”
Conference Paper -
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Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates
Published 2024“…The method is compared to the existing optimization methods in machine learning, namely stochastic gradient descent method (SGD) and Adam. …”
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Conference or Workshop Item