Search Results - (( generation classifications learning algorithm ) OR ( using function methods algorithm ))

Functional link neural network with modified bee-firefly learning algorithm for classification task by Mohmad Hassim, Yana Mazwin

“…The standard learning method for tuning weights in FLNN is Backpropagation (BP) learning algorithm. …”
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New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

“…Also, the proposed models for learning in data sets generated the classification rules faster than other methods. …”
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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review by Nur Farahaina, Idris, Mohd Arfian, Ismail

“…There are several learning algorithms to implement the decision tree but the most commonly-used is ID3 algorithm. …”
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Modified anfis architecture with less computational complexities for classification problems by Talpur, Noureen

“…Furthermore, researchers have mainly used metaheuristic algorithms to avoid the problem of local minima in standard learning method. …”
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A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani by Mahmoud Reza, Saybani

“…The increasing size of data being stored have created the need for computer-based methods for automatic data analysis. 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

“…Total rules number, rules length and rules accuracy for the generation rules are recorded. 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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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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Fault classification in smart distribution network using support vector machine by Chuan O.W., Ab Aziz N.F., Yasin Z.M., Salim N.A., Wahab N.A.

“…In this paper, a machine-learning algorithm known as Support Vector Machine (SVM) for fault type classification in distribution system has been developed. …”

The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

“…The implementation of pre-processing algorithms has been demonstrated to be able to mitigate the signal noises that arises from the winking signals without the need for the use signal filtering algorithms. …”
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

“…From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
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Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach by Qayyum A., Saeed Malik A., Saad N.M., Iqbal M., Abdullah M.F., Rasheed W., Abdullah T.A.B.R., Bin Jafaar M.Y.

Deep learning-based classification of breast tumors in ultrasound images / Ayub Ahmed Omar by Ayub Ahmed, Omar

“…The use of ultrasound imaging techniques to diagnose breast cancer at an early stage is a popular and effective method. …”
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FIS-PNN: a hybrid computational method for protein-protein interactions prediction using the secondary structure information by Sakhinah Abu Bakar, Javid Taheri, Albert Y Zomaya

“…As a result, they must interact with each other. In this study we used our approach, namely FIS-PNN, to predict the interacting proteins in yeast from the information of their secondary structures using hybrid machine learning algorithms. …”
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Noise eliminated ensemble empirical mode decomposition scalogram analysis for rotating machinery fault diagnosis by Atik, Faysal

“…The ability of CNN was compared with two traditional machine learning algorithms, k nearest neighbour (kNN) and the support vector machine (SVM), using statistical features from EEMD, CEEMD and NEEEMD. …”
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A framework of modified adaptive neuro-fuzzy inference engine by Hossen, Md. Jakir

“…The Takagi-Sugeno-Kang (TSK) type fuzzy inference system was chosen and constructed by an automatic generation of clusters as well as membership functions and minimal rules through the use of hybrid fuzzy clustering and the modified apriori algorithms respectively. …”
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Extreme Learning Machine neural networks for multi-agent system in power generation by Yaw C.T., Wong S.Y., Yap K.S., Tan C.H.

“…Extreme Learning Machine (ELM) is widely known as an effective learning algorithm than the conventional learning methods from the point of learning speed as well as generalization. …”

Incisor Malocclusion Using Cut-out Method And Convolutional Neural Network by Muhamad Farhin Harun, Azurah A Samah, Muhammad Imran Ahmad Shabuli, Hairudin Abdul Majid, Haslina Hashim, Nor Azman Ismail, Syiral Mastura Abdullah, Aspalilah Alias

Forensic language of property theft genre based on mathematical formulae and machine learning algorithms / Hana' Abd Razak by Abd Razak, Hana'

“…Convolution Neural Network (CNN) using deep learning algorithm is chosen in identifying frequency of movement and execution time of housebreaking crime. …”
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An interpretable fuzzy-ensemble method for classification and data analysis / Adel Lahsasna by Adel, Lahsasna

“…iv The proposed method is tested using six data sets from the UCI machine learning repository, and the obtained results are compared with other benchmark methods. …”
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Predictive Framework for Imbalance Dataset by Megat Norulazmi, Megat Mohamed Noor

“…The major contribution of this research is a step by step guideline which consists of methods/approaches in generating a prediction for process materials.…”
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