Search Results - (( developing building mining algorithm ) OR ( java data normalization algorithm ))
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1
Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…Even a normal people using clustering to grouping their data. …”
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2
Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak
Published 2021“…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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3
Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer
Published 2017“…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
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5
Data mining in network traffic using fuzzy clustering
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6
Classification of liver disease diagnosis: a comparative study
Published 2013“…MDM involves developing data mining algorithms and techniques to analyze medical data. …”
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7
Stock price monitoring system
Published 2024“…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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8
SANAsms: Secure short messaging system for secure GSM mobile communication
Published 2008“…The system is developed using Java 2 Micro Edition (J2ME) which is written in Java. …”
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9
Building classification models from imbalanced fraud detection data / Terence Yong Koon Beh, Swee Chuan Tan and Hwee Theng Yeo
Published 2014“…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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10
Tracking student performance in introductory programming by means of machine learning
Published 2023Conference Paper -
11
Improved building roof type classification using correlation-based feature selection and gain ratio algorithms
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12
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Electing the best set of features will help to improve the classifier predictions in terms of the normal and abnormal pattern. The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. …”
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13
Analysis of Traffic Accident Patterns Using Association Rule Mining
Published 2024“…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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Machine learning for data classification in construction project planning
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16
Feature selection in intrusion detection, state of the art: A review
Published 2016“…With irrelevant and redundant features learning algorithm builds detection model with less accuracy rate. …”
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17
Enhanced mechanism to handle missing data of Hadith classifier
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18
Challenges of hidden data in the unused area two within executable files
Published 2009“…The designed algorithms were intended to help in proposed system aim to hide and retract information (data file) with in unused area 2 of any execution file(exe.file). …”
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Integrated framework with association analysis for gene selection in microarray data classification
Published 2011“…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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20
Understanding the occurrence of metastatic breast cancer through clinical, phenotype and genotype data, and the employment of machine learning / Nadia Jalaludin
Published 2023“…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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