Search Results - (( java application tree algorithm ) OR ( encoder implementation learning algorithm ))
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Computational Technique for an Efficient Classification of Protein Sequences With Distance-Based Sequence Encoding Algorithm
Published 2017“…Machine learning is being implemented in bioinformatics and computational biology to solve challenging problems emerged in the analysis and modeling of biological data such as DNA, RNA, and protein. …”
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Motion learning using spatio-temporal neural network
Published 2020“…In this study, learning is implemented on a reward basis without the need for learning targets.The algorithm has shown good potential in learning motion trajectory particularly in noisy and dynamic settings. …”
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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images
Published 2024“…In the third classification algorithm, hybrid features are extracted using AlexNet and VGG-16 through a transfer learning approach where parameter manipulation is implemented to simplify the network. …”
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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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Auxiliary-based extension of multi-tasking sequence-to-sequence model for chatbot answers
Published 2021“…“SEQ2SEQ++” is a Seq2Seq MTL learning method which comprises of four (4) components (“Multi-Functional Encoder” (MFE), “Answer Decoder”, “Answer Encoder”, “Ternary-Classifier” (TC)) and is trained using “Dynamic Weights” algorithm and “Comprehensive Attention Mechanism” (CAM). …”
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Spatio-temporal event association using reward-modulated spike-time-dependent plasticity
Published 2018“…The results demonstrate that the algorithm can also learn temporal sequence detection.Learning has also been tested in face-voice association using real biometric data.The loose dependency between the model's anatomical properties and functionalities could offer a wide range of applications, especially in complex learning environments.…”
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Mining Sequential Patterns using I-PrefixSpan
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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Exploring employee working productivity: initial insights from machine learning predictive analytics and visualization / Mohd Norhisham Razali ... [et al.]
Published 2023“…Data from an academic institution were collected and pre-processed by encoding relevant features before applying various machine learning predictive models. …”
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Prediction of COVID-19 outbreak using Support Vector Machine / Muhammad Qayyum Mohd Azman
Published 2024“…In response to the unprecedented challenges posed by the COVID-19 pandemic, this research project presents a systematic approach to outbreak prediction, specifically advocating for the implementation of Support Vector Machine (SVM) algorithms. …”
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Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. The general idea of I-PrefixSpan is to use the efficient data structure for general tree-like framework and separator database to reduce the execution time and memory usage. …”
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AI powered asthma prediction towards treatment formulation: an android app approach
Published 2022“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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AI powered asthma prediction towards treatment formulation : An android app approach
Published 2022“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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Exploring employee working productivity: initial insights from machine learning predictive analytics and visualization
Published 2023“…Data from an academic institution were collected and pre-processed by encoding relevant features before applying various machine learning predictive models. …”
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Development of brain tumor segmentation of magnetic resonance imaging (MRI) using u-net deep learning
Published 2023“…The algorithm consists of three parts; the first part, the downsampling part, the bottleneck part, and the optimum part. …”
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Improved personalised data modelling using parameter independent fuzzy weighted k-nearest neighbour for spatio/spectro-temporal data
Published 2021“…Therefore, a data modelling mechanism which implements PIfwkNN classifier algorithm for improving the overall classification accuracy of the NeuCube architecture has been proposed. …”
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