Search Results - (( using classification methods algorithm ) OR ( basic classification mining algorithm ))
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1
Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…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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2
Mining The Basic Reproduction Number (R0) Forecast For The Covid Outbreak
Published 2022“…The COVID-19 Basic Reproduction Number, R0 a predictive model is developed using a linear regression classification algorithm to predict the COVID-19 Basic Reproduction Number, Robased on the actual COVID-19 Basic Reproduction Number, R0. …”
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Monograph -
3
Review of Wheat Disease Classification and Severity Detection Models
Published 2023“…To combat these diseases, researchers have been studying the use of advanced techniques such as deep plant disease learning and image processing methods for identification. …”
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4
An ensemble feature selection method to detect web spam
Published 2018“…In addition, it improves classification metrics in comparison to basic feature selection methods.…”
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5
Improved normalization and standardization techniques for higher purity in K-means clustering
Published 2016“…The K-means algorithm is a famous and fast technique in non-hierarchical cluster algorithms. …”
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6
Hybrid Neural Network With K-Means For Forecasting Response Candidate In Direct Marketing
Published 2014“…This study proposed hybrid Neural Network (NN) methods in data mining to support direct marketing analysis and forecast. …”
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7
Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…There are several learning algorithms to implement the decision tree but the most commonly-used is ID3 algorithm. …”
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8
Case Slicing Technique for Feature Selection
Published 2004“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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9
A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network
Published 2014“…Third, using a modified k-Nearest Neighbor method as well as an improved method of backpropagation neural networks, the classification process was advanced based on optimum arrays of the features selected by genetic algorithms. …”
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10
Overview of metaheuristic: classification of population and trajectory
Published 2010“…An algorithm that applies a metaheuristic method is used when there are no specific methods to find a solution. …”
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11
Utilizing artificial bee colony algorithm as feature selection method in Arabic text classification
Published 2023“…One of the widely used algorithms for feature selection in text classification is the Evolutionary algorithm . …”
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12
Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier
Published 2018“…There are a lot of feature extraction methods and classification methods for iris classification. …”
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13
An efficient algorithm for cardiac arrhythmia classification using ensemble of depthwise Separable convolutional neural networks
Published 2020“…Using our proposed method, the four stages of ECG classification, i.e., QRS detection, preprocessing, feature extraction, and classification, were reduced to two steps only, i.e., QRS detection and classification. …”
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14
Development of a fingerprint gender classification algorithm using fingerprint global features
Published 2016“…This study is meant to enhance the forensic manual method by proposing a new algorithm for fingerprint global feature extraction for gender classification. …”
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15
Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms
Published 2021“…The objective of this study is to perform DM classification using various machine learning algorithms using Weka as a tool. …”
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Final Year Project -
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…The comparison showed that, the accuracy of the unsupervised classification map with value of 88.4% that was generated by using the cluster labelling algorithm was slightly more than the maximum-likelihood supervised classification map with value of 87.5%. …”
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17
Breast cancer disease classification using fuzzy-ID3 algorithm with FUZZYDBD method: automatic fuzzy database definition
Published 2021“…FUZZYDBD method, an automatic fuzzy database definition method, would be used to design the fuzzy database for fuzzification of data in the FID3 algorithm. …”
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18
Real-time Traffic Classification Algorithm Based on Hybrid of Signature Statistical and Port to Identify Internet Applications
Published 2014“…Most of the current classification methods were only valid for offline classification. …”
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An efficient and effective case classification method based on slicing
Published 2006“…The paper also studies the comparison between the proposed method and the two selected classification algorithms using several domains.…”
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20
Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd
Published 2022“…Classification is a data mining technique used to classify varied data types according to a specific criterion. …”
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