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Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak by Ishak, Najihah Salsabila

“…A classifier model is developed using Naive Bayes characteristics. A comparison between built-in Scikit Learn Naive Bayes algorithm, and the scratch Naive Bayes algorithm is used to measure its effectiveness in terms of accuracy. …”
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Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer by Tuerxun, Adilijiang

“…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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Data mining in network traffic using fuzzy clustering by Mohamad, Shamsul

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Data mining in network traffic using fuzzy clustering by Mohamad, Shamsul

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Classification of liver disease diagnosis: a comparative study by Bahramirad, Sina, Mustapha, Aida, Eshraghi, Maryam

“…MDM involves developing data mining algorithms and techniques to analyze medical data. …”
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Stock price monitoring system by Ng, Chun Ming

“…As stock price is time series data, a time series prediction algorithm is being utilized to build a deep learning model, namely Long Short-Term Memory (LSTM). …”
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Building classification models from imbalanced fraud detection data / Terence Yong Koon Beh, Swee Chuan Tan and Hwee Theng Yeo by Terence, Yong Koon Beh, Swee, Chuan Tan, Hwee, Theng Yeo

“…Many real-world data sets exhibit imbalanced class distributions in which almost all instances are assigned to one class and far fewer instances to a smaller, yet usually interesting class. Building classification models from such imbalanced data sets is a relatively new challenge in the machine learning and data mining community because many traditional classification algorithms assume similar proportions of majority and minority classes. …”
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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.

Improved building roof type classification using correlation-based feature selection and gain ratio algorithms by Norman, M., Mohd Shafri, Helmi Zulhaidi, Pradhan, Biswajeet, Yusuf, B.

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Analysis of Traffic Accident Patterns Using Association Rule Mining by Yudy, Pranata, Tri Basuki, Kurniawan, Edi Surya, Negara, Ahmad Haidar, Mirza

“…This study analyzed the levels of minor, moderate, and severe traffic accidents in the Palembang Police area from 2015 to 2020 using association rule mining and the apriori algorithm. The study established valuable insights into accident trends and contributing factors by leveraging traffic accident data and determining variable relationships. …”
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Enhancing obfuscation technique for protecting source code against software reverse engineering by Mahfoudh, Asma

“…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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Intent-IQ: customer’s reviews intent recognition using random forest algorithm by Mazlan, Nur Farahnisrin, Ibrahim Teo, Noor Hasimah

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Machine learning for data classification in construction project planning by Lau, Zheng Liang

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Feature selection in intrusion detection, state of the art: A review by Rais, H.M., Mehmood, T.

“…With irrelevant and redundant features learning algorithm builds detection model with less accuracy rate. …”
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Enhanced mechanism to handle missing data of Hadith classifier by Aldhlan, Kawther A., Zeki, Ahmed M., Zeki, Akram M.

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Integrated framework with association analysis for gene selection in microarray data classification by Ong, Huey Fang

“…Modifications have been made on the existing association algorithm for mining frequent itemsets, where genes in each itemset were sorted according to their discriminative scores rather than according to lexicographic order. …”
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Understanding the occurrence of metastatic breast cancer through clinical, phenotype and genotype data, and the employment of machine learning / Nadia Jalaludin by Jalaludin, Nadia

“…Therefore, the objective of this study is to: a) mine and integrate clinical, phenotype and genotype data that contributes to the occurrence of MBC, b) build a prediction model that can predict possibility of occurrence to metastatic state of breast cancer based on factors previously determined in (a), and c) to validate findings from (a) and (b) through systematic review of randomised controlled trials of MBC. …”
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A Rough Set-Based Approach for Identifying and Replacing Missing Concepts in Incomplete Sentences in Computer Domain Texts by Nur Faiqah ‘Aqilah binti Fuaad

Improving Extreme Programming Framework With Security Concerns For E-Commerce Applications by Bala, Musa Shuaibu

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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