Search Results - (( programming feature selection algorithm ) OR ( java _ function algorithm ))

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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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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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.

Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun by Kok , Sun Sun

“…Whereas the process of examining through the web pages, retrieving and searching the relevant data in a liTML page, and selecting the best satisfying data are based on the features and operations of the Genetic Algorithms.…”
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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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Comparison of Recursive Feature Elimination and Boruta as Feature Selection in Greenhouse Gas Emission Data Classification by Riko, Febrian, Anne Mudya, Yolanda

“…The results indicate that classification performance improves with feature selection and recursive feature elimination compared to scenarios without feature selection or with Boruta feature selection. …”
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A Toolkit for Simulation of Desktop Grid Environment by FOROUSHAN, PAYAM CHINI

“…The prototypes will be developed using JAVA language united with a MySQL database. Core functionality of the simulator are job generation, volunteer generation, simulating algorithms, generating graphical charts and generating reports. …”
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Fingerprint verification using clonal selection algorithm / Farah Syadiyah Shamsudin by Shamsudin, Farah Syadiyah

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Software metrics selection model for predicting maintainability of object-oriented software using genetic algorithms by Bakar, Abubakar Diwani

“…The latest effort to solve this selection problem is the development of the metrics selection model that uses genetic algorithm (GA). …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

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Real-time algorithmic music composition application. by Yap, Alisa Yi Hui

“…This project is about the study of evolutionary music, and focuses on the development of an algorithmic music composer using the Java programming language. …”
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Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

“…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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Melanoma skin cancer recognition using negative selection algorithm / Muhammad Rushamir Hakimi Ruslan by Ruslan, Muhammad Rushamir Hakimi

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A stylometry approach for blind linguistic steganalysis model against translation-based steganography by Mohd Lokman, Syiham

“…However, accuracy of blind steganalysis algorithms highly depend on the features selected from the input data especially when attacking embedding techniques in TBS. …”
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Feature clustering for pso-based feature construction on high-dimensional data by Swesi, Idheba Mohamad Ali Omer, Abu Bakar, Azuraliza

“…Therefore, the main purpose of this paper is to select the most informative features and construct new features from the selected features for a better classification performance. …”
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation by Mat Jani H., Lee S.P.

Comparison of performances of Jaya Algorithm and Cuckoo Search algorithm using benchmark functions by Ahmed, Mashuk, Nasser, Abdullah B., Kamal Z., Zamli, Heripracoyo, Sulistyo

“…This paper aims to compare the performance of two metaheuristic algorithms which are Jaya Algorithm (JA) and Cuckoo Search (CS) using some common benchmark functions. …”
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Parallel computation of maass cusp forms using mathematica by Chan, Kar Tim

“…Some features that appear in the plots are explained. We have also compared the performance of parallel programming and normal programming here in order to justify the feasibility and advantages of using the parallel version of commercially available software for complex computations of Maass cusp forms. …”
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Book recommendation system using content-based filtering / Amalin Aliesya Mohd Azmi by Mohd Azmi, Amalin Aliesya

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Image classification using two dimensional wavelet coefficients with parallel computing by Ong, Yew Fai

“…This research algorithm demonstrated a very promising result with Support Vector Machines, this algorithm produces a 90% of accuracies whereas the decision tree algorithm gets 100% accuracies. …”
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