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1
Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…However, Laplacian regularization lacks extrapolating power and biases the solution towards a constant function. These drawbacks affect the performances of Laplacian regularized semi-supervised ELMs when a few labeled data is used. …”
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2
Support directional shifting vector: A direction based machine learning classifier
Published 2021“…The positional error of the linear function has been modelled as a loss function which is iteratively optimized using the gradient descent algorithm. …”
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3
Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…In data mining, classification learning is broadly categorized into two categories; supervised and unsupervised. …”
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4
A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules
Published 2013“…Benchmark data sets from various fields were used to test the proposed algorithms. …”
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5
Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…Nevertheless, there are some limitations in ID3 algorithm that can affect the performance in the classification of data. …”
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New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…It is a useful approach for uncovering classificatory knowledge and building a classification rules. …”
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7
Jogging activity recognition using k-NN algorithm
Published 2022“…The k-NN algorithm is a simple and easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems. …”
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An improved algorithm for iris classification by using support vector machine and binary random machine learning
Published 2018“…In machine learning, there are three type of learning branch that can used in classification procedures for data mining. …”
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A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…Various data mining techniques are being used by researchers of different domains to analyze data and extract valuable information from a data set for further use. …”
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10
Development of Hybrid Convolutional Neural Network and Radial Basis Function for Autism Spectrum Disorder Classification
Published 2024“…Hence, this study proposed hybrid deep learning algorithms for ASD classification. Two algorithms merged: U-net neural network and Radial Basis Function (RBF) for medical image segmentation. …”
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11
Computational Technique for an Efficient Classification of Protein Sequences With Distance-Based Sequence Encoding Algorithm
Published 2017“…The major problems in classifying protein sequences into existing families/superfamilies are the following: the selection of a suitable sequence encoding method, the extraction of an optimized subset of features that possesses significant discriminatory information, and the adaptation of an appropriate learning algorithm that classifies protein sequences with higher classification accuracy. …”
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12
Improved cuckoo search based neural network learning algorithms for data classification
Published 2014“…Artificial Neural Networks (ANN) techniques, mostly Back-Propagation Neural Network (BPNN) algorithm has been used as a tool for recognizing a mapping function among a known set of input and output examples. …”
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13
An improvement of back propagation algorithm using halley third order optimisation method for classification problems
Published 2020“…While H-DFP, the highest improvement achieved in generalisation accuracy is on the Seeds classification with 41.73% improvement for 70:30 data division. …”
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14
Intent-IQ: customer’s reviews intent recognition using random forest algorithm
Published 2025“…Two machine learning model is chosen to build the classification models which are Random Forest (RF) algorithm and Multinomial Naïve Bayes (MNB) algorithm. …”
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Anomaly detection in ICS datasets with machine learning algorithms
Published 2021“…The features of flow-based network traffic are extracted for behavior analysis with port-wise profiling based on the data baseline, and anomaly detection classification and prediction using machine learning algorithms are performed.…”
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An ensemble data summarization approach based on feature transformation to learning relational data
Published 2015“…The Information Gain borrowed from Information Retrieval theory and Term-term Correlation algorithm are used to determine the relevancy of these features to be selected or merged in order to form a new generation of TF-IDF vector space. …”
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17
Development of machine learning-based algorithm to determine the condition in transformer oil
Published 2021“…Classification learning app used to train DGA data divided into three categories fault, Not determined (N/D) and stray gassing. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)
Published 2024“…Therefore, in this study a new optimized variant of machine learning algorithms is presented. …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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20
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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