Search Results - (( java implication tree algorithm ) OR ( using simple ((using algorithm) OR (mining algorithm)) ))
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Predicting future sales using genetic algorithm: data mining sales / Siti Hajar Yaacob
Published 2014“…Tool decision tree calculate the stock based on the number of product order. This research using Simple Genetic Algorithm which is involved crossover and fitness. …”
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A numerical method for frequent pattern mining
Published 2009“…The PC_Miner algorithm traverses the PC_Tree by using an efficient pruning technique. …”
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Logistic regression methods for classification of imbalanced data sets
Published 2012“…This thesis aims to develop the simple and effective imbalanced classification algorithms by previously improving the algorithms performance of general classifiers i.e. …”
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Dissimilarity algorithm on conceptual graphs to mine text outliers
Published 2009“…In Comparison to other text outlier detection method, this approach managed to capture the semantics of documents through the use of CGs and is convenient to detect outliers through a simple dissimilarity function.Furthermore, our proposed algorithm retains a linear complexity with the increasing number of CGs.…”
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Data mining techniques for disease risk prediction model: A systematic literature review
Published 2023Conference Paper -
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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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Ant colony algorithm for web page classification
Published 2008“…Ant Miner II is the used algorithm. It also propose a simple text preprocessing technique to reduce the large numbers of attributes associated with web content mining, without dealing linguistic complications. …”
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A comparative study of the classification of skin burn depth in human
Published 2017“…Empirical results showed that the best classification algorithms that were able to classify most of the burn depths using a supplied test set were Logistic, Simple Logistic, MultiClassClassifier, OneR, and LMT, with an average accuracy of 68.9% whereas for 10-fold cross validation evaluation, the best result was obtained through the Simple Logistic algorithm with an average accuracy of 73.2%. …”
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Building classification models from imbalanced fraud detection data / Terence Yong Koon Beh, Swee Chuan Tan and Hwee Theng Yeo
Published 2014“…We evaluated the models generated from seven classification algorithms with two simple data balancing techniques. …”
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A direct ensemble classifier for imbalanced multiclass learning
Published 2012“…Researchers have shown that although traditional direct classifier algorithm can be easily applied to multiclass classification, the performance of a single classifier is decreased with the existence of imbalance data in multiclass classification tasks.Thus, ensemble of classifiers has emerged as one of the hot topics in multiclass classification tasks for imbalance problem for data mining and machine learning domain.Ensemble learning is an effective technique that has increasingly been adopted to combine multiple learning algorithms to improve overall prediction accuraciesand may outperform any single sophisticated classifiers.In this paper, an ensemble learner called a Direct Ensemble Classifier for Imbalanced Multiclass Learning (DECIML) that combines simple nearest neighbour and Naive Bayes algorithms is proposed. …”
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Enhancing predictive crime mapping model using association rule mining for geographical and demographic structure
Published 2014“…The other 40% of the dataset is used to test generated rules. A simple program of C++ is implemented using Microsoft Visual Studio to test generated rules until accuracy of performance is obtained. …”
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Forecast of Muslimah fashion trends in Caca's company / Muhammad Saifullah Mohd Taip
Published 2023“…The results showed that the decision tree algorithm had a higher accuracy of 100% for category prediction, 47% for colour prediction, and 65% for size prediction, while the random forest algorithm had a higher accuracy of 100% for category prediction, 85% for colour prediction, and 91% for size prediction. …”
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Arabic text classification using hybrid feature selection method using chi-square binary artificial bee colony algorithm
Published 2021“…After that, the wrapper method, Artificial Bee Colony algorithm, is used as the second level where Naive Base is used as a fitness function. …”
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A hybrid approach to semi-supervised named entity recognition in health, safety and environment reports
Published 2009“…The UTP's HSE reports are the investigation reports which contain the information on incidents and accidents occurred during the daily operations. Many algorithms have been reported for NER ranging from simple statistical methods to advanced Natural language Processing (NLP) methods. …”
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Data Analysis and Rating Prediction on Google Play Store Using Data-Mining Techniques
Published 2022“…The goal of using a Decision Tree is to create a training model that can use to predict the class or value of the target variable by learning simple decision rules inferred from prior data. …”
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Simple quantum circuit for pattern recognition based on nearest mean classifier
Published 2016“…Lett. 114, 140504 (2015)] which uses quantum matrix inverse algorithm to find optimal hyperplane that separated two different classes. …”
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Extracting Tweets Using R in The Context of Ethical Issues
Published 2021“…For further work, it is possible to use text mining activities and sentiment analysis approaches, as well as explore various social media platforms using R packages for decision makings…”
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Proceeding Paper -
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Data Mining Approach To Classify Covid-19 Severity By Clinical Symptoms
Published 2021“…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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Information extraction using Link Grammar
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