Search Results - (( pattern machine algorithm ) OR ( between ((mining algorithm) OR (search algorithm)) ))

Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

“…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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Genetic Algorithm for Web Data Mining by Loo, Kevin Teow Aik

“…Therefore, this study attempted to discover any association between the word types or the information types used to search through the World Wide Web using the available search engines. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling by Alfred, Rayner, Loo, Yew Jie, Obit, Joe Henry, Lim, Yuto, Haviluddin, Haviluddin, Azman, Azreen

“…Then, the mapping percentages between the predefined and produced clusters are used to assess the performance of the proposed algorithm. …”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

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Social media mining: a genetic based multiobjective clustering approach to topic modelling by Rayner Alfred, Loo Yew Jie, Joe Henry Obit, Yuto Lim, Haviluddin Haviluddin, Azreen Azman

“…Then, the mapping percentages between the predefined and produced clusters are used to assess the performance of the proposed algorithm. …”
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RARE: mining colossal closed itemset in high dimensional data by Md Zaki, Fatimah Audah, Zulkurnain, Nurul Fariza

“…The task of mining association rules highly relies on the efficiency of the algorithms to extract all frequent itemsets that exist in the database. …”
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud by Shariff, S. Sarifah Radiah, Hud, Hady

“…Secondly, in solving every Machine Learning problem, there is no one algorithm superior to other algorithms. …”
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A prototype for context identification of scientific papers via agent-based text mining by Mahmoud M.A., Ahmad M.S.

Traditional marble game using ant colony optimization / Muhammad Izzat Imran Che Isa by Che Isa, Muhammad Izzat Imran

“…The more number of marbles, the higher the search accuracy. In future, traditional marble game can be applied with other search algorithm to optimize the solution…”
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Data Mining for Building Neural Protein Sequence Classification Systems with Improved Performance by Wang, Dianhui, Lee, Nung Kion, Dillon, Tharam S.

“…Traditionally, two protein sequences are classified into the same class if their feature patterns have high homology. These feature patterns were originally extracted by sequence alignment algorithms, which measure similarity between an unseen protein sequence and identified protein sequences. …”
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A filtering algorithm for efficient retrieving of DNA sequence by Abdul Rahman, Mohd Nordin, Mohd. Saman, Md. Yazid, Ahmad, Aziz, Md. Tap, Abu Osman

“…Similarity search procedure is executed by an alignment process between query and targeted sequences. …”
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

“…Meanwhile, Kmeans clustering algorithm has also been reported has widely known for solving most unsupervised classification problems. …”
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Improvement DACS3 Searching Performance using Local Search by Md Rais, Helmi, Ali Othman, Zulaiha, Hamdan, Abdul Razak

“…Three supportive strategies are used such as dynamic candidate list, elitist ants and pheromone trail smoothing whereas improvement strategies used local search. The capability of DACS3 is measured based on quality of solution, time taken to reach the solution and algorithm performance. …”
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A hybrid Method Of Centroid-Based Clustering And Meta-Heuristic For Personalized Web Search by Bourair Sadik Mohamad Taqi

Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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Classification of cervical cancer using random forest by Bahirah, Mohd Bashah, Ku Muhammad Naim, Ku Khalif, Nor Azuana, Ramli

“…Model evaluation has been conducted to identify the robust data mining algorithm in the prediction of cervical cancer risk. …”
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Finger Motion In Classifying Offline Handwriting Patterns by Yeoh, Shen Horng

“…Therefore, this study aims to relate the finger movements to handwriting patterns. The specific objectives include: (i) to determine whether finger motion attributes can distinguish patterns of handwriting, (ii) classify handwriting patterns by sentence inclination based on different finger motion, (iii) to investigate the rule-reasoning statements between the finger motion and the handwriting inclinations. …”
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A comparative study between rough and decision tree classifiers by Mohamad Mohsin, Mohamad Farhan

“…Theoretically, a good set of knowledge should provide good accuracy when dealing with new cases.Besides accuracy, a good rule set must also has a minimum number of rules and each rule should be short as possible.It is often that a rule set contains smaller quantity of rules but they usually have more conditions.An ideal model should be able to produces fewer, shorter rule and classify new data with good accuracy.Consequently, the quality and compact knowledge will contribute manager with a good decision model.Because of that, the search for appropriate data mining approach which can provide quality knowledge is important.Rough classifier (RC) and decision tree classifier (DTC) are categorized as RBC.The purpose of this study is to investigate the capability of RC and DTC in generating quality knowledge which leads to the good accuracy.To achieve that, both classifiers are compared based on four measurements that are accuracy of the classification, the number of rule, the length of rule, and the coverage of rule.Five dataset from UCI Machine Learning namely United States Congressional Voting Records, Credit Approval, Wisconsin Diagnostic Breast Cancer, Pima Indians Diabetes Database, and Vehicle Silhouettes are chosen as data experiment.All datasets were mined using RC toolkit namely ROSETTA while C4.5 algorithm in WEKA application was chosen as DTC rule generator.The experimental results indicated that both classifiers produced good classification result and had generated quality rule in different types of model – higher accuracy, fewer rule, shorter rule, and higher coverage.In term of accuracy, RC obtained higher accuracy in average while DTC significantly generated lower number of rule than RC.In term of rule length, RC produced compact and shorter rule than DTC and the length is not significantly different.Meanwhile, RC has better coverage than DTC.Final conclusion can be decided as follows “If the user interested at a variety of rule pattern with a good accuracy and the number of rule is not important, RC is the best solution whereas if the user looks for fewer nr, DTC might be the best choice”…”
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An analysis of text mining factors enhancing the identification of relevant studies by Khashfeh M., Mahmoud M.A., Ahmad M.S.

“…The third process is the parsing that is operated by a text mining algorithm. The last part is the storage that is managed by Monitor Agent. …”

Hybridised Network of Fuzzy Logic and a Genetic Algorithm in Solving 3-Satisfiability Hopfield Neural Networks by Farah Liyana, Azizan, Saratha, Sathasivam, Majid Khan, Majahar Ali, Nurshazneem, Roslan, Caicai, Feng

“…This work proposed a new hybridised network of 3-Satisfiability structures that widens the search space and improves the effectiveness of the Hopfield network by utilising fuzzy logic and a metaheuristic algorithm. …”
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