Search Results - (( basic implementation svm algorithm ) OR ( java application tree algorithm ))
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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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Raspberry Pi-Based Finger Vein Recognition System Using PCANet
Published 2018“…However, performance comparison between kNN, kGNN and SVM shows that kNN is more suitable for FVRS implementation. …”
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Monograph -
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Mining Sequential Patterns using I-PrefixSpan
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Citation Index Journal -
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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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Thesis -
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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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Conference or Workshop Item -
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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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Real-time oil palm fruit bunch ripeness grading system using image processing techniques
Published 2013“…Feature extraction for oil palm FFB colour, texture, and thorns was implemented by using statistical colour features, colour histogram, grey-level co-occurrence matrices (GLCM), basic grey level aura matrix technique (BGLAM), and Gabor wavelet techniques on the three different regions of interest (ROIs), namely, ROI1, ROI2, and ROI3. …”
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