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1
Using fuzzy association rule mining in cancer classification
Published 2011“…A new algorithm has been developed to identify the fuzzy rules and significant genes based on fuzzy association rule mining. …”
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2
Relationship between psycho-maturity and performance of sepak takraw
Published 2020“…The Louvain clustering algorithm is used to categorise the players to high, medium and low psycho-matured players based on seven fundamental psychological measures, viz. maturity status, selftalk, activation, imagery, emotion control, automaticity and goal setting. …”
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3
An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA
Published 2025“…However, these algorithms often fall short in consistently detecting and classifying network intrusions, particularly when distinctions between classes are subtle or when facing evolving attack patterns. …”
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4
Pemetaan Pm10 Dan Aot Menggunakan Teknik Penderiaan Jauh Di Semenanjung Malaysia
Published 2006“…The two-band model, terma linear and modified algorithms were selected based on the highe.st correlation coefficient (R) value {> 80%) and the lowest root-mean-square (RMS) error value. …”
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5
Investigation of features for classification RFID reading between two RFID reader in various support vector machine kernel function
Published 2022“…Instead, the distance verses RSSI algorithm is used to determine the objects to be located based on the distance of the tag to be located to each reader. …”
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6
Drought-events and potential impacts on land use/land cover dynamics based on AVHRR data of 1992-2003 for central Iran
Published 2011“…At the second phase, a seasonal-based classification algorithm for AVHRR (Advanced Very High Resolution Radiometer) data developed to enhance the classification accuracy. …”
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7
Predicting Cheaters in PlayerUnknown’s Battlegrounds (PUBG) using Random Forest Algorithm
Published 2023“…The research methodology involves the collection of a comprehensive data set from Kaggle containing a variety of gameplay features. Patterns and relationships between input variables and cheating behaviours are analysed through the application of supervised learning techniques, specifically a classification model. …”
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8
Identification model for hearing loss symptoms using machine learning techniques
Published 2014“…The model is implemented using both unsupervised and supervised machine learning techniques in the form of Frequent Pattern Growth (FP-Growth) algorithm as feature transformation method and multivariate Bernoulli naïve Bayes classification model as the classifier. …”
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9
Deep plant: A deep learning approach for plant classification / Lee Sue Han
Published 2018“…They look for the procedures or algorithms that maximize the use of leaf databases for plant predictive modelling, but this results in leaf features which are liable to change with different leaf data and feature extraction techniques. …”
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10
Classification with degree of importance of attributes for stock market data mining
Published 2004“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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11
A novel ensemble decision tree-based CHi-squared Automatic Interaction Detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping
Published 2014“…An ensemble algorithm of data mining decision tree (DT)-based CHi-squared Automatic Interaction Detection (CHAID) is widely used for prediction analysis in variety of applications. …”
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12
Herbal plant image classification using transfer learning and fine-tuning deep learning model
Published 2024“…Different hyperparameters were used across the various experiment settings, and the authors observed the behavior and relationships of the distinct models, datasets, and hyperparameters toward the classification task's accuracy. …”
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13
Relationship between psycho-maturity and performance of sepak takraw
Published 2020“…Different random forest classifiers were developed to classify the players based on the aforesaid psychological measures. It was shown that the optimised model could provide reasonable discrimination between the players with a classification accuracy of 82.61% on the test dataset, suggesting the significance of the psychological indicators towards the performance of the players.…”
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14
Driver behaviour classification: a research using OBD-II data and machine learning
Published 2024“…Then, the proposed model makes use of the K-Means algorithm to create driving behaviour labels whether belong to safe or aggressive - validated by the safety score criteria. …”
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15
Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration
Published 2014“…Finally the relationship between conditioning factors were assessed and the landslide susceptibility map (LSM) was produced. …”
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16
An adaptive ant colony optimization algorithm for rule-based classification
Published 2020“…Differing from other complex and difficult classification models, rules-based classification algorithms produce models which are understandable for users. …”
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17
Footwear quality evaluation using decision tree and logistic regression models
Published 2022“…Then, various types of decision trees and logistic regression model are developed to gain the best classification model for predicting footwear quality performance. …”
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18
Knowledge base processing method based on text classification algorithm
Published 2023“…The text classification algorithm's knowledge base processing method utilizes existing data from the knowledge base to guide the construction and training of the classification model. …”
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19
A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network
Published 2014“…The performance of the proposed model was compared with thirteen well-known classification models based on seven datasets. …”
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20
Herbal plant image classification using transfer learning and fine-tuning deep learning model
Published 2024“…Different hyperparameters were used across the various experiment settings, and the authors observed the behavior and relationships of the distinct models, datasets, and hyperparameters toward the classification task's accuracy. …”
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