Search Results - (( programming subset selection algorithm ) OR ( java data normalization algorithm ))

Towards a better feature subset selection approach by Shiba, Omar A. A.

“…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
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Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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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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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

“…Even a normal people using clustering to grouping their data. …”
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SANAsms: Secure short messaging system for secure GSM mobile communication by Anuar, N.B., Azlan, I.M., Wahid, A.W.A., Zakaria, O.

“…The system is developed using Java 2 Micro Edition (J2ME) which is written in Java. …”
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BFEDroid: A Feature Selection Technique to Detect Malware in Android Apps Using Machine Learning by Chimeleze C., Jamil N., Ismail R., Lam K.-Y., Teh J.S., Samual J., Akachukwu Okeke C.

Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…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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Feature clustering for pso-based feature construction on high-dimensional data by Swesi, Idheba Mohamad Ali Omer, Abu Bakar, Azuraliza

“…The Redundancy-Based Feature Clustering (RFC) algorithm was applied to choose the most informative features from the original data, while PSO was used to construct new features from those selected by RFC. …”
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Challenges of hidden data in the unused area two within executable files by Naji, Ahmed Wathik, Zaidan, A.A., Zaidan, B.B.

“…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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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

“…Two sets of experimental data involving 20 diabetic patients and 20 healthy subjects were collected from CITO laboratory Semarang Central Java, Indonesia. …”
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Development of optimized maintenance scheduling model for coal-fired power plant boiler by Noor Fazreen Binti Ahmad Fuzi, Ms.

“…In this thesis, two different approaches, Mixed Integer Linear Programming (MILP) and Particle Swarm Optimization (PSO) were selected to solve the maintenance schedule and optimization problems in coal-fired power plant boilers. …”

Reservoir Inflow Forecasting Using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System Techniques by Googhari, Shahram Karimi

“…The selected ANFIS model gives lower values in most of the performance indices during training. …”
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