Search Results - (( parameter evaluation method algorithm ) OR ( quality classification problem algorithm ))
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1
Aco-based feature selection algorithm for classification
Published 2022“…However, the MGCACO algorithm has three main drawbacks in producing a features subset because of its clustering method, parameter sensitivity, and the final subset determination. …”
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2
Software defect prediction framework based on hybrid metaheuristic optimization methods
Published 2015“…For the purpose of this study, ten classification algorithms have been selected. The selection aims at achieving a balance between established classification algorithms used in software defect prediction. …”
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3
Extremal region detection and selection with fuzzy encoding for food recognition
Published 2019“…The performance of algorithms was measured based on classification accuracy, error rate, and precision and recall. …”
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4
Evaluation of land use land cover changes impacts on water quality at Nerus River using geospatial techniques / Noor Azzatul Najwa Azman
Published 2021“…The method that used to do the classification for each year is supervised classification. …”
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5
An enhanced gated recurrent unit with auto-encoder for solving text classification problems
Published 2020“…However, GRU suffered from three major issues when it is applied for solving the text classification problems. The first drawback is the failure in data dimensionality reduction, which leads to low quality solution for the classification problems. …”
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6
Improving multi-resident activity recognition in smart home using multi label classification with adaptive profiling
Published 2018“…In accordance to the mentioned problem, Label Combination (LC) of multi label classification is introduced because of its ability to transform the multi label problem into 2ᶫ multi-class problem and exploit the correlation between the class labels. …”
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7
Classification model for water quality using machine learning techniques
Published 2015“…This article proposes a suitable classification model for classifying water quality based on the machine learning algorithms. …”
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8
An adaptive ant colony optimization algorithm for rule-based classification
Published 2020“…Various classification algorithms have been developed to produce classification models with high accuracy. …”
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9
Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems
Published 2015“…The outcome positively demonstrates that the hybrid algorithm is able to improve the classification performance with a smaller number of hidden nodes and is effective in multiclass classifi cation problems.Furthermore, the results indicate that the proposed hybrid method is a potentially useful classifi er for enhancing the classification process ability when compared with the multiobjective genetic algorithm based on the TBP network (MOGATBP) and certain other methods found in the literature.…”
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10
Hybrid NSGA-II Optimization for Improving the Three-Term BP Network for Multiclass Classification Problems
Published 2015“…The outcome positively demonstrates that the hybrid algorithm is able to improve the classification performance with a smaller number of hidden nodes and is effective in multiclass classifi cation problems. …”
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11
Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach
Published 2009“…The quality of a given classification technique is measured by the computational complexity, execution time of algorithms, and the number of patterns that can be classified correctly despite any distribution. …”
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12
Intent-IQ: customer’s reviews intent recognition using random forest algorithm
Published 2025“…In order to overcome this problem, a classification model for intent recognition is developed. …”
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13
BAT-BP: A new BAT based back-propagation algorithm for efficient data classification
Published 2016“…One of the nature inspired meta-heuristic Bat algorithm is becoming a popular method in solving many complex optimization problems. …”
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14
Real-time oil palm fruit bunch ripeness grading system using image processing techniques
Published 2013“…The purpose of which was to investigate the relationship between the external features and ripeness of different oil palm FFB types as well as to test and validate the implementation of oil palm grading system methods and techniques. Special grading system with specific methods and techniques was built with fast, accurate, and objective ripeness classification to work with the parameters and properties of oil palm FFB, which is important for the farmers to have an objective classifier before selling their product as well as the oil palm companies to classify correctly the quality of oil palm fruit bunches due to the variations in different oil palm qualities. …”
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15
Power quality problem classification based on Wavelet Transform and a Rule-Based method
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16
A De-noising Scheme for Enhancing Power Quality Problem Classification System Based on Wavelet Transform and Rule-Based Method
Published 2011“…Using the de-noising scheme proposed in this paper, a higher tolerance to noise can be achieved by the Power Quality Problem Classification system.…”
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17
Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This reserarch adapted a methodology of computer vision and algorithms that exploit image segmentation, feature extraction and fuzzy classification to guide the research activities. …”
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18
Ant colony optimization for rule induction with simulated annealing for terms selection
Published 2012“…This paper proposes a sequential covering based algorithm that uses an ant colony optimization algorithm to directly extract classification rules from the data set.The proposed algorithm uses a Simulated Annealing algorithm to optimize terms selection, while growing a rule.The proposed algorithm minimizes the problem of a low quality discovered rule by an ant in a colony, where the rule discovered by an ant is not the best quality rule, by optimizing the terms selection in rule construction. …”
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19
New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…Thus, the challenge is how to develop an efficient model that can decrease the learning time without affecting the quality of the generated classification rules. Huge information systems or data sets usually have some missing values due to unavailable data that affect the quality of the generated classification rules. …”
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20
A modified weighted support vector machine (WSVM) to reduce noise data in classification problem
Published 2021“…Classification refers to a predictive modeling problem where a class label is predicted for a given example of input data. …”
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