Search Results - (( data extraction method algorithm ) OR ( data reduction methods algorithm ))

Towards lowering computational power in IoT systems: Clustering algorithm for high-dimensional data stream using entropy window reduction by Alkawsi G., Al-amri R., Baashar Y., Ghorashi S., Alabdulkreem E., Kiong Tiong S.

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A new ant based rule extraction algorithm for web classification by Ku-Mahamud, Ku Ruhana, Saian, Rizauddin

“…Web documents contain enormous number of attributes as compared to other type of data. Ant-Miner algorithm is also still lacking in efficiency, accuracy and rule simplicity because of the local minima problem.Therefore, the Ant-Miner algorithm needs to be improved by taking into consideration of the accuracy and rule simplicity criteria so that it could be used to classify Web documents data sets or any large data sets.The best attribute selection method for Web texts categorization is the combination of correlation-based evaluation with random search as the search method.However, this attribute selection method will not give the best performance in attributes reduction. …”
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A fast feature extraction algorithm for image and video processing by Abdulhussain, Sadiq H., Ramli, Abdul Rahman, Mahmmod, Basheera M., Saripan, M. Iqbal, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Baker, Thar, Flayyih, Wameedh Nazar, Jassim, Wissam A.

“…Therefore, high processing time for that sheer volume of data will be required. Image and video applications demand for reduction in computational cost (processing time) when extracting features. …”
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Fatigue Features Extraction of Road Load Time Data Using the S-Transform by S., Abdullah, Che Ku Eddy Nizwan, Che Ku Husin, M. F. M., Yunoh, M. Z., Nuawi, Z. M., Nopiah

“…This paper presents the algorithm development of a new fatigue data editing technique using S-T approach. …”
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A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani by Mahmoud Reza, Saybani

“…Many researchers, who have developed methods and algorithms within the field of artificial intelligence, machine learning and data mining, have addressed extracting useful information from the data. …”
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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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Efficient classifying and indexing for large iris database based on enhanced clustering method by Khalaf, Emad Taha, Mohammed, Muamer N., Kohbalan, Moorthy, Khalaf, Ahmad Taha

“…From the experimental results, the proposed method was indeed more effective for clustering and classification and outperformed the traditional k-mean algorithm. …”
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New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

“…Two different models for learning in data sets were proposed based on two different reduction algorithms. …”
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Data mining reduction methods and performances of rules by Ahmad, Faudziah, Basir, Mohammad Aizat

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Supervised ANN classification for engineering machined textures based on enhanced features extraction and reduction scheme by Ashour, Mohammed Waleed, Khalid, Fatimah, Al-Obaydee, Mohammed

“…The proposed methodology focuses mainly on three main stages for an input image, firstly extracting features by commonly used features extraction methods such as edge detection, and histogram. …”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves by Lia, Kamelia

“…The proposed method integrates colour and texture feature-based image analysis with machine learning algorithms for classification. …”
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Non-fiducial based ECG biometric authentication using one-class support vector machine by Hejazi, Maryamsadat, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Hashim, Shaiful Jahari, Abdul Aziz, Ahmad Fazli, Singh, Yashwant Prasad

“…This paper investigates the effect of different parameters of data set size, labeling data, configuration of training and testing data sets, feature extraction, different recording sessions, and random partition methods on accuracy and error rates of these SVM classifiers. …”
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FAILURE PREDICTION OF ENGINEERING PROBLEMS USING INTERACTIVE COMPUTING NOTEBOOK ENVIRONMENT by FLORINA LING, CASTELO

“…Prediction model built based on regression problem using dimensionality reduction method and regression algorithms. Dimensionality reduction would extract only important features for more accurate prediction. …”
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Object-based imagery analysis for automatic urban tree species detection using high resolution satellite image by Shojanoori, Razieh

“…The method of maximum likelihood classification and support vector machines leads to the lowest classification accuracy since these algorithms extract only the spectral information of each pixel and consequently fail to utilize spatial, color and textural information.…”
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A new model for iris data set classification based on linear support vector machine parameter's optimization by Faiz Hussain, Zahraa, Ibraheem, Hind Raad, Alsajri, Mohammad, Ali, Ahmed Hussein, Mohd Arfian, Ismail, Shahreen, Kasim, Sutikno, Tole

“…In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
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Finger vein verification system using repeated line tracking and dimensionality reduction using PCA algorithms with SURF matching by Ei Wei., Ting, M. Z., Ibrahim, D.J., Mulvaney

“…Then, the vein pattern was extracted using Repeated Line Tracking (RLT). The feature vector of the vein pattern was then dimensionality reduction by Principal Component Analysis (PCA). …”
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P300 detection of brain signals using a combination of wavelet transform techniques by Motlagh, Farid Esmaeili

“…In this research the BCI competition data-set has been processed through 5 optimized detection methods. …”
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Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction by Al-Himyari, Bayadir Abbas

“…A fitness function is proposed to deal with multi-objective problem without weight using a new composition method. The model was compared to other learning algorithms for NFS such as Fuzzy c-means (FCM) and grid partition algorithm. …”
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Multispectral palm vein image fusion for contactless palm vein verification system by Soh, Shi Chuan

“…SIFT algorithm achieved a reduction in EER rate by 12% in 700 nm, 8% in 850 nm, 7% in 940 nm compared with the SURF algorithm. …”
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Adaptive Similarity Component Analysis in Nonparametric Dynamic Environment by Sojodishijani, Omid

“…From a dimensionality reduction evaluation aspect, the average misclassification error of the proposed method in low-rank feature space is 9.6% and same error rate for three other well-known feature extraction methods is 21.21%. …”
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