Search Results - (( pattern classification problems algorithm ) OR ( using combination based algorithm ))
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1
Classification for large number of variables with two imbalanced groups
Published 2020“…This study proposed two algorithms of classification namely Algorithm 1 and Algorithm 2 which combine resampling, variable extraction, and classification procedure. …”
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2
Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…Hence, this situation is believed in yielding of decreasing the classification accuracy. In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
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3
Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…It involves development of Max-Min Rule-Based Classification Algorithm. The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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4
Evaluation and optimization of frequent association rule based classification
Published 2014“…Deriving useful and interesting rules from a data mining system is an essential and important task. Problems such as the discovery of random and coincidental patterns or patterns with no significant values, and the generation of a large volume of rules from a database commonly occur. …”
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5
Classification of credit card holder behavior using K Nearest Neighbor algorithm / Ahmad Faris Rahimi
Published 2017“…This indicates that the performance of KNN is acceptable and promising in this classification problem. Since KNN is the simplest form of artificial intelligence, future work could combine this algorithm with other classification algorithm. …”
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6
Ant colony algorithm for text classification in multicore-multithread environment / Ahmad Nazmi Fadzal
Published 2017“…Pheromone concept is the main criterion that distinguish ACO to other algorithms. Based on the concept, pheromone saturation is used to combine stackable solution pattern that is discovered while straying to different term node to build a path. …”
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7
An improved multiple classifier combination scheme for pattern classification
Published 2015“…Combining multiple classifiers are considered as a new direction in the pattern recognition to improve classification performance. …”
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8
Non-invasive pathological voice classifications using linear and non-linear classifiers
Published 2010“…Two types of experiments are conducted using the proposed feature extraction and classification algorithms. …”
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9
A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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10
Ant system-based feature set partitioning algorithm for classifier ensemble construction
Published 2016“…In this study, Ant system-based feature set partitioning algorithm for classifier ensemble construction is proposed.The Ant System Algorithm is used to form an optimal feature set partition of the original training set which represents the number of classifiers.Experiments were carried out to construct several homogeneous classifier ensembles using nearest mean classifier, naive Bayes classifier, k-nearest neighbor and linear discriminant analysis as base classifier and majority voting technique as combiner. …”
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11
Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah
Published 2021“…To solving pattern classification problem, the optimization deep learning architecture and parameter by using four convolution layers is set up to classify the three pathological signs; HEM, MA and exudate. …”
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12
On equivalence of FIS and ELM for interpretable rule-based knowledge representation
Published 2023Article -
13
Improving hand written digit recognition using hybrid feature selection algorithm
Published 2022“…Therefore, many researchers have applied and developed various machine learning algorithms that could efficiently tackle the handwritten digit recognition problem. …”
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14
Hybrid Models Of Fuzzy Artmap And Qlearning For Pattern Classification
Published 2015“…A variety of benchmark problems are used for evaluation of individual and ensemble QFAM-based models. …”
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15
A COMBINED HISTOGRAM OF ORIENTED GRADIENTS AND COMPLETED LOCAL BINARY PATTERN METHODS FOR PEOPLE COUNTING IN A DENSE CROWD SCENARIO
Published 2016“…This method used a collaborative Histogram of Oriented Gradients (HOG) and Completed Local Binary Pattern (CLBP) based on people detection algorithm to detect headshoulder region. …”
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16
Pattern generation through feature values modification and decision tree ensemble construction
Published 2013“…The ensemble of decision trees based on the proposed technique was evaluated using a suite of 30 benchmark classification problems, and was found to achieve performance better than or competitive with related conventional methods. …”
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17
Compacted dither pattern codes over MPEG-7 dominant colour descriptor in video visual depiction
Published 2010“…The algorithmic comparison between the two is presented in this paper, and demonstrates that there are several competitive advantages of CDPC in feature extraction and classification stages when compared to MPEG-7 DCD. …”
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18
Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…In pattern recognition system, achieving high accuracy in pattern classification is crucial. …”
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19
Integrated framework with association analysis for gene selection in microarray data classification
Published 2011“…The main challenge in building this classification system is the curse of dimensionality problem. …”
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20
Tracking and recognizing the activity of multi resident in smart home environments
Published 2017“…We perform experiments on real world multi resident on ARAS Dataset and shows that the LC (Label Combination) using Decision Tree (DT) as base classifier can tackle the above problems.…”
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