Search Results - (( moderation classification methods algorithm ) OR ( java implementation mining algorithm ))

Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

“…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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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…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 by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

“…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 by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

“…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 by Lee, Quan

“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Classification of basal stem rot disease in oil palm using dielectric spectroscopy by Al-Khaled, Al-Fadhl Yahya Khaled

“…Without implementing any data reduction algorithm, the highest classification accuracy was found in SVM classifier with 79.55%. …”
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An intra-severity classification and adaptation technique to improve dysarthric speech recognition accuracy / Bassam Ali Qasem Al-Qatab by Bassam Ali Qasem, Al-Qatab

“…The algorithms include Linear Discriminant Analysis (LDA), Artificial Neural Network (ANN), Support Vector Machine (SVM), Naive Bayes (NB), Classification And Regression Tree (CART), Random Forest (RF). …”
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Non-invasive gliomas grading using swarm intelligence algorithm / Muhammad Harith Ramli by Ramli, Muhammad Harith

“…Bat algorithm is chosen for the development of the prototype for segmentation and classification purpose. …”
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Mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm by Liaghat, Shohreh, Mansor, Shattri, Ehsani, Reza, Mohd Shafri, Helmi Zulhaidi, Meon, Sariah, Sankaran, Sindhuja

“…The selected principal component scores were used in classification using linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), k-nearest neighbor (kNN) and Naive-Bayes (NB) multivariate classification algorithms. …”
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Backpropagation vs. radial basis function neural model : Rainfall intensity classification for flood prediction using meteorology data by Chai, S.S., Wong, W.K., Goh, K.L.

“…Accurate prediction of this variable would save human lives and properties. Soft computing methods have been widely applied in this field. Among the various soft computing methods, Artificial Neural Network (ANN) is the most commonly used methodology. …”
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Automatic diabetic retinopathy detection and classification system by Omar, Zainab Awatif, Hanafi, Marsyita, Mashohor, Syamsiah, Mahfudz, Nur Faten Munirah, Abdul Muna'aim, Maimunah

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Diabetic retinopathy detection using fusion of textural and optimized convolutional neural network features / Uzair Ishtiaq by Uzair , Ishtiaq

“…The hybrid approach based on image preprocessing and fusion of features is the foundation of the proposed classification method. The preprocessing steps involved in this study include image resizing, data augmentation, applying median filter and image sharpening. …”
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Recommendation System Model For Decision Making in the E-Commerce Application by Mohammed Mahmudur Rahman

Computer aided diagnoses for detecting the severity of Keratoconus by Abdullah, Osamah Qays, Boughariou, Aicha, Al-Azawi, Fadia W., Al-Araji, Ahmed Mohammed Khadum Abdulamer, Mehdy, Mehdy Mwaffeq

“…Disease severity was categorized into three stages, namely, mild, moderate, and severe, according to the topographic KC classification by a senior ophthalmologist. …”
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Data Mining Approach To Classify Covid-19 Severity By Clinical Symptoms by Kanyan, Laura Jasmine Thomas

“…Missing values were treated using filtering and imputation methods. The classification algorithms: J48, SMO, Random Forest, and Simple Logistic were executed and tested to classify data into three classes: mild, moderate, and severe. …”
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Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease by Che Hashim, Izrahayu

“…In an imbalanced dataset, one of the two classes contains fewer total samples than the other class. The sampling-based method, also known as the data level method, is used to deal with this problem. …”
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Assessment of near-infrared and mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm plantation by Liaghat, Shohreh

“…Results confirmed the usefulness and efficiency of spectra-based classification approach for fast screening of BSR.…”
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Complexity Analysis of EEG in Patients With Social Anxiety Disorder Using Fuzzy Entropy and Machine Learning Techniques by Al-Ezzi, A., Al-Shargabi, A.A., Al-Shargie, F., Zahary, A.T.

“…The main objective of this study is to analyze the electroencephalogram (EEG) complexity of 88 SAD subjects, subdivided into 4 balanced groups (22 severe, 22 moderate, 22 mild, and 22 healthy controls (HCs) using Fuzzy Entropy measure (FE) and machine learning algorithms. …”
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