Search Results - (( java implementation tree algorithm ) OR ( using _ ((missing algorithm) OR (mining algorithm)) ))
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…These data are processed and stored in appropriate formats in a MySQL server database. 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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Exploratory analysis with association rule mining algorithms in the retail industry / Alaa Amin Hashad ... [et al.]
Published 2024“…The FP-Growth algorithm was found to be faster and more effective than the Apriori algorithm in extracting frequent item sets and generating association rules. …”
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3
Auto-feed hyperparameter support vector regression prediction algorithm in handling missing values in oil and gas dataset
Published 2020“…This problem inspires the idea to develop a prediction algorithm to predict the missing values in the dataset, where Support vector regression (SVR) has been proposed as a prediction method to predict missing values in several academic types of researches. …”
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Enhanced mechanism to handle missing data of Hadith classifier
Published 2011“…Decision tree algorithms have the ability to deal with missing values or wrong data. …”
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Proceeding Paper -
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Data Mining Analysis Of Chronic Kidney Disease (CKD) Level
Published 2022“…Adding the uncertain class the best accuracy obtained was 98.5% using the SMO algorithm. A predictive classification model that determines the accuracy for three classification classes was developed accordingly using the SMO algorithm.…”
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Monograph -
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A Rough Set-Based Approach for Identifying and Replacing Missing Concepts in Incomplete Sentences in Computer Domain Texts
Published 2026thesis::master thesis -
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Discovering optimal clusters using firefly algorithm
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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Thesis -
9
DEVELOPMENT OF MULTI-VERSE OPTIMIZER IN ARTIFICIAL NEURAL NETWORK FOR ENHANCING THE IMPUTATION ACCURACY OF DAILY RAINFALL OBSERVATIONS
Published 2024“…MVOFNN is compared against the conventional Levenberg-Marquardt Feedforward Neural Network (LMFNN) and a promising data mining-based imputation approach, the Regularized Expectation Maximization (RegEM) algorithm, to assess its reliability and feasibility in reconstructing missing daily rainfall data. …”
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Book Chapter -
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Data Mining Approach To Classify Covid-19 Severity By Clinical Symptoms
Published 2021“…Data pre-processing was carried out to identify and remove outliers. Missing values were treated using filtering and imputation methods. …”
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Monograph -
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An Optimized ANN Measure-Correlate-Predict Method for Long-term Wind Prediction in Malaysia
Published 2023Conference Paper -
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Development of intelligent hybrid learning system using clustering and knowledge-based neural networks for economic forecasting : First phase
Published 2004“…We proposed KMeans clustering algorithm that is based on multidimensional scaling, joined with neural knowledge based technique algorithm for supporting the learning module to generate interesting clusters that will generate interesting rules for extracting knowledge from stock exchange databases efficiently and accurately.…”
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Conference or Workshop Item -
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Sentiment analysis of customer review for Tina Arena Beauty
Published 2025“…Future work may involve expanding the dataset, integrating real-time feedback systems, and evaluating advanced algorithms to improve classification performance further. …”
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Student Project -
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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Thesis -
15
Determination of the Best Single Imputation Algorithm for Missing Rainfall Data Treatment
Published 2016“…Consequently, a competent imputation algorithm for missing data treatment algorithm is very much needed. …”
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Missing tags detection algorithm for radio frequency identification (RFID) data stream
Published 2019“…Thus in this research, an AC complement algorithm with hashing algorithm and Detect False Negative Read algorithm (DFR) is used to developed the Missing Tags Detection Algorithm (MTDA). …”
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Thesis -
17
Determination of the best single imputation algorithm for missing rainfall data treatment
Published 2016“…Consequently, a competent imputation algorithm for missing data treatment algorithm is very much needed. …”
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Missing Value Imputation for PM10 Concentration in Sabah using Nearest Neighbour Method(NNM) and Expectation-Maximization (EM) Algorithm
Published 2020“…The missing data is imputed by using both NNM and EM algorithm. …”
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Systematic review on missing data imputation techniques with machine learning algorithms for healthcare
Published 2022“…Many machine learning algorithms have been applied to impute missing data with plausible values. …”
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An Evaluation of Machine Learning Algorithms for Missing Values Imputation
Published 2019“…It represents the research and imputation of missing values in gene expression data. By using the local or global correlation of the data we focus mostly on the contrast of the algorithms. …”
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