Search Results - (( sequence classification based algorithm ) OR ( data classification using algorithm ))
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Computational Technique for an Efficient Classification of Protein Sequences With Distance-Based Sequence Encoding Algorithm
Published 2017“…In this article, we have proposed a distance-based sequence encoding algorithm that captures the sequence's statistical characteristics along with amino acids sequence order information. …”
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Optimized tree-classification algorithm for classification of protein sequences
Published 2016“…In this work, we have proposed an optimized tree-classification technique which uses cluster k nearest neighbor classification algorithm to classify protein sequences into superfamilies. …”
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3
Optimized tree-classification algorithm for classification of protein sequences
Published 2016“…In this work, we have proposed an optimized tree-classification technique which uses cluster k nearest neighbor classification algorithm to classify protein sequences into superfamilies. …”
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4
An improved particle swarm optimization algorithm for data classification
Published 2023“…Optimisation-based methods are enormously used in the field of data classification. …”
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Data mining of protein sequences with amino acid position-based feature encoding technique
Published 2014“…The classification results indicate that the proposed encoding technique with a decision tree classification algorithm has achieved 85.9 classification accuracy over the Yeast protein sequence dataset. …”
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Deep learning-based colorectal cancer classification using augmented and normalised gut microbiome data / Mwenge Mulenga
Published 2022“…At the same time, there has been growing interest from the research community in machine learning based detection of diseases using sequence based on gut microbiome data. …”
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A new LoRa based positioning algorithm utilizing sequence based deep learning technique
Published 2023“…Next, RSSI and Signal-to-Noise Ratio (SNR) that is measured is being classified whether it is LoS or NLoS environment based on the sequence-based Bi-LSTM model. Furthermore, an analysis of classification using different sequence length is done. …”
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An efficient computational intelligence technique for classification of protein sequences
Published 2014“…The classification accuracy of 88.7 was achieved over the Yeast protein sequence data taken from the well-known UniProtKB database. …”
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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. …”
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification
Published 2012“…Classification performance can be improved by implementing a reliability threshold for training data. …”
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Classification and detection of intelligent house resident activities using multiagent
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Development of Phasor Measurement Unit Based Fault Detection and Faulty Line Classification in Electrical Power System
Published 2019“…This model implements Non-Recursive Phasor Estimation (NRPE) algorithm. Secondly, the study proposes an index for faulty node classification (FNC) based on the positive sequence voltage (PSV) measurements of the pre-fault and post-fault conditions. …”
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Deep learning object detector using a combination of Convolutional Neural Network (CNN) architecture (MiniVGGNet) and classic object detection algorithm
Published 2020“…MiniVGGNet is an architecture network used to train an object classification, and the data used for this purpose was collected from specific indoor environment building. …”
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Evaluation and optimization of frequent, closed and maximal association rule based classification
Published 2014“…Real world applications of association rule mining have well-known problems of discovering a large number of rules, many of which are not interesting or useful for the application at hand.The algorithms for closed and maximal item sets mining significantly reduce the volume of rules discovered and complexity associated with the task, but the implications of their use and important differences with respect to the generalization power, precision and recall when used in the classification problem have not been examined.In this paper, we present a systematic evaluation of the association rules discovered from frequent, closed and maximal item set mining algorithms, combining common data mining and statistical interestingness measures, and outline an appropriate sequence of usage.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data/items, and detailed evaluation of rule sets is provided as a whole and w.r.t individual classes. …”
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An accurate algorithm of PMU-based wide area measurements for fault detection using positive-sequence voltage and unwrapped dynamic angles
Published 2022“…The algorithm includes an index for faulty bus classification based on the positive-sequence voltage measurements of the pre-fault and post-fault conditions, where the bus with a maximum differential percentage is identified as a faulted bus. …”
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Analyzing RNA-Seq gene expression data using deep learning approaches for cancer classification
Published 2022“…In the last phase, classification is performed, and eight DL algorithms are used. …”
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Angle Based Protein Tertiary Structure Prediction Using Bees Optimization Algorithm
Published 2010“…WEKA program application was used for main chain angles (Phi and Psi) data classification. …”
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Improving multi-resident activity recognition in smart home using multi label classification with adaptive profiling
Published 2018“…Furthermore, there is tendency that multi label classifications used instead of traditional single label classification technique. …”
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