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Classification algorithms
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A deep learning approach combining autoencoder with supervised classifiers for IoT anomaly detection
Anomaly detection for Internet of things (IoT) networks is a challenging issue due to the huge number of devices that connect to each other and generate huge amounts of data. In this study, we propose a model combining Autoencoder (AE) with classification algorithms to build an endto-end architecture for processing, feature extraction and data classification.
13p
viambani
18-06-2024
6
1
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In this volume the methodological aspects of the scenario logic and probabilistic (LP) non-success risk management are considered. The theoretical bases of scenario non-success risk LP-management in business and engineering are also stated. Methods and algorithms for the scenario risk LP-management in problems of classification, investment and effectiveness are described.
15p
vimeyers
29-05-2024
3
2
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The paper "Applying machine learning algorithms to classify forest cover type from sentinel 2 MSI data" presents the results of forest cover classification in Dak Lak province from Sentinel 2 optical satellite image data using machine learning techniques. Sentinel 2 MSI images taken in November 2015 and December 2020 are used to classify forest cover objects and then evaluate forest cover changes in the period 2015-2020.
12p
tukhauquantuong1011
22-04-2024
5
3
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The research "Application of random forest algorithm and google colab for land cover classification" is to provide the approach RF with Google Colab environment for classifying land cover in Quang Binh province, Vietnam using sentinel - 2 image in August 2021. The results have indicated the ability of this research direction with an overall accuracy above 80 %.
9p
tukhauquantuong1011
22-04-2024
6
2
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Identifying essential genes in genome-wide loss-of-function screens is a critical step in functional genomics and cancer target finding. We previously described the Bayesian Analysis of Gene Essentiality (BAGEL) algorithm for accurate classification of gene essentiality from short hairpin RNA and CRISPR/Cas9 genome-wide genetic screens.
11p
vibransone
28-03-2024
1
1
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Part 1 book "Scheduling algorithms" includes content: Classification of scheduling problems, some problems in combinatorial optimization, computational complexity, single machine scheduling problems, parallel machines.
166p
muasambanhan05
22-01-2024
3
3
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Early detection of skin cancer matters because diagnosis, prognosis and treatment plan differ for each skin cancer type at their stages. Medical imaging taking the advantages of the non-invasive and non-ionizing polarized light is emerging as a tool for the development of screening and diagnotic tests.
7p
vimichaelfaraday
28-12-2023
6
3
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This scholarly research paper addresses the crucial and complex challenge of detecting and categorizing Internet of Things (IoT) botnets through the utilization of machine learning algorithms. The study is focused on conducting meticulous analysis and manipulation of IoT botnet data, with a specific emphasis placed on the widely acknowledged IoT23 dataset.
12p
visystrom
22-11-2023
7
5
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Ebook "Neural networks - Algorithms, applications, and programming techniques" includes content: Introduction to ANS technology, adaline and madaline, backpropagation, the BAM and the hopfield memory, simulated annealing, the counter propagation network, self organizing maps, adaptive resonance theory, spatiotemporal pattern classification, the neocognitron.
414p
haojiubujain07
20-09-2023
5
2
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Attribute reduction is one important part researched in rough set theory. A reduct from a decision table is a minimal subset of the conditional attributes which provide the same information for classification purposes as the entire set of available attributes.
16p
vimulcahy
18-09-2023
3
2
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Data clustering is applied in various fields such as document classification, dental Xray image segmentation, medical image segmentation, etc. Especially, clustering algorithms are used in satellite image processing in many important application areas, including classification of vehicles participating in traffic, logistics, classification of satellite images to forecast droughts, floods, forest fire, etc.
15p
vimulcahy
18-09-2023
2
2
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This study proposes a distributed classification framework, which adapts supervised SelfOrganizing Maps (SOM) as base learners. The supervised SOM is the integration of the SOM algorithm with the Learning Vector Quantization (LVQ) algorithm, so called SOM-LVQ model. Multiple SOM-LVQ models are created using different feature subsets, each of which represents one different local information source.
6p
viannee
02-08-2023
6
4
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Develop an approach, One-class-at-a-time, for triaging psychiatric patients using machine learning on textual patient records. Our approach aims to automate the triaging process and reduce expert effort while providing high classification reliability.
7p
visteverogers
24-06-2023
3
2
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This study demonstrated an approach for mapping land-use/land-cover by combining Landsat-8 images with a high-quality reference dataset in a classification model using the Support Vector Machine algorithm.
8p
vinebula
02-06-2023
6
2
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Decision tree classification algorithms have significant potential in classifying remote sensing data. This article’s approach method using decision tree technology to classify remote sensing images with the representative object as oil spill.
12p
viironman
02-06-2023
5
3
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In this paper, we propose using PCA for dimension reduction and then using decesion tree algorithms to search the space of eigenvectors with the goal of selecting a subset of eigenvectors encoding important information.
4p
vifalcon
18-05-2023
7
2
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This paper proposed a new model of emergency controls load shedding based on the fast identification of the unstable state of the power system. K-means clustering algorithm divided the instability mode into the clusters. The results of analysis of this cluster were used as the basis for classification control.
9p
vidoctorstrange
06-05-2023
4
1
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This paper proposes a Multilayer Feed forward Neural Network (MLFNN) for speech classification in a smart electric wheelchair, in which with extraction of speech commands is performed using a Mel Frequency Cepstral Coefficients (MMFC) method.
7p
vidoctorstrange
06-05-2023
7
4
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Lynch syndrome is a hereditary cancer syndrome associated with high risks of colorectal and endometrial cancer that is caused by pathogenic variants in the mismatch repair genes (MLH1, MSH2, MSH6, PMS2, EPCAM).
8p
vinarcissa
21-03-2023
3
1
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In this paper, we build an incremental algorithm to find the approximate reduct according to the combined filter-wrapper approach. Experimental results on a number of sample datasets show that the proposed incremental algorithm is more efficient than some other incremental algorithms following the filter approach in terms of the number of reductive set attributes and classification accuracy.
8p
vineville
08-02-2023
6
2
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