Search Results - (( develop educational tree algorithm ) OR ( java application mining algorithm ))

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

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Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

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Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

“…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 by Lee, Quan

“…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 by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

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Phylogenetic tree classification system using machine learning algorithm by Tan, Jia Kae

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C4.5 Algorithm Application for Prediction of Self Candidate New Students in Higher Education by Erlan, Darmawan

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First Semester Computer Science Students’ Academic Performances Analysis by Using Data Mining Classification Algorithms by Azwa, Abdul Aziz, Fadhilah, Ahmad

“…From the experiment, the models develop using Rule Based and Decision Tree algorithm shows the best result compared to the model develop from the Naïve Bayes algorithm. …”
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Visualisasi pohon sintaksis berasaskan model dan algoritma sintaks ayat bahasa Melayu by Yusnita, Muhamad Noor

“…It can be concluded that the algorithm and model proposed were useful for the development of the prototype. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…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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E4ML: Educational Tool for Machine Learning by Sainin, Mohd Shamrie, Siraj, Fadzilah

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Tracking student performance in introductory programming by means of machine learning by Khan I., Al Sadiri A., Ahmad A.R., Jabeur N.

Mobile Learning: An Application Prototype for AVL Tree Learning Object by Ibrahim, Mohammad Noor, Mahamad, Saipunidzam, Chua, Edrea Ning Wei

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Prediction of electronic cigarette and vape use among Malaysian: decision tree analysis by Kartiwi, Mira, Ab Rahman, Jamalludin, Nik Mohamed, Mohamad Haniki, Draman, Samsul, Ab Rahman, Norny Syafinaz

“…The predictive model was developed using Induction Decision Tree (ID3) algorithm, a popular data mining technique an exploratory tool for knowledge discovery. …”
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Predictive modelling of student academic performance using machine learning approaches : a case study in universiti islam pahang sultan ahmad shah by Nurul Habibah, Abdul Rahman

“…Recently, predictive analytics research has grown in popularity in higher education because it provides helpful information to educators and potentially assists them in enhancing student achievement. …”
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An artificial intelligence approach to monitor student performance and devise preventive measures by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

“…In addition, the prediction model is transformed into a clear shape to make it easy for the instructor to prepare the necessary precautionary procedures. We developed a set of prediction models with distinct machine learning algorithms. …”

A simultaneous spam and phishing attack detection framework for short message service based on text mining approach by Mohd Foozy, Cik Feresa

“…There are five (5) Classification techniques used such as Naive Bayes, K-NN, Decision Tree, Random Tree and Decision Stump. The result of Hybrid Feature accuracy using Rapidminer and Naive Bayes technique is 77.47%, for K-NN: 78.56%, Decision Tree: 57.16%, Random Tree: 57.24% and Decision Stump: 57.16%. …”
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Exploring students' performance in mathematics in Portugal using data analytics techniques: a data science use-case by Hassan, Raini, Fadzleey, Nur Zulfah Insyirah, Ab Hamid, Annesa Maisarah, Abd Aziz, Rabiatul Adawiyah, Jamalullain, Afiefah, Syaiful 'Adli, Fatin Syafiqah

“…The practical application of this research lies in developing predictive models that inform data- driven decisions by educators and policymakers. …”
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Poverty risk prediction based on socioeconomic factors using machine learning approach by Mohd Zawari, Nur Farhana Adibah

“…A secondary dataset that considered 635 households of Terengganu was used, and the following aspects were identified as important indicators of poverty: age, income, education, occupation, and health. Information gain was used in the feature selection and four classification algorithms namely, Logistic Regression, Random Forest, Decision Tree, and Gradient Boosted, were implemented and tested with the incorporation of 10-fold cross-validation and splitting 70:30 in WEKA. …”
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