Machine learning techniques for data mining: A survey

Sharma, Seema; Agrawal, Jitendra; Agarwal, Shikha; Sharma, Sanjeev

doi:10.1109/iccic.2013.6724149

Cited by 57 publications

(26 citation statements)

References 14 publications

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“…Linear classification methods also include the support vector machine method (SVM) [13,14]. This method is successfully applied in various problems, since the classification is carried out in a space of a higher dimension than the dimension of the original feature space.…”

Section: Linear Classification Methodsmentioning

confidence: 99%

Applying methods of machine learning in the task of intrusion detection based on the analysis of industrial process state and ICS networking

Sokolov¹,

Pyatnitsky²,

Alabugin³

2019

FME Transactions

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Modern industrial control systems (ICS) are increasingly becoming targets of cyber attacks. Traditional security tools based on a signature approach are not always able to detect a new attack, the signature of which has not yet been described. In particular, this occurs during targeted attacks on industrial facilities. Cyber attacks can cause anomalies in the operation of an industrial control system and process equipment under its control. Therefore, to detect attacks, it is advisable to use an approach based on the detection of anomalies. A reasonable way to implement this approach is to use machine learning techniques. The paper deals with the most common methods of machine learning (decision tree algorithms, linear algorithms, support vector machine) and neural networks. To assess their applicability in the problem of detection of ICS anomalies, the Additional Tennessee Eastman Process Simulation Data for Anomaly Detection Evaluation and Gas Pipeline datasets were used.

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Section: Linear Classification Methodsmentioning

confidence: 99%

Applying methods of machine learning in the task of intrusion detection based on the analysis of industrial process state and ICS networking

Sokolov¹,

Pyatnitsky²,

Alabugin³

2019

FME Transactions

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“…There are various fields where Data Mining is applicable to greater extends such as medical, advertising, telecommunications, stock etc. This paper indicates different classification methods utilized as a part of many fields, for example, Decision Tree, Bayesian Network, Nearest Neighbour, Support Vector Machine (SVM) [3]. By and large decision trees and support vector machines have diverse operational profiles, where one is extremely precise the other isn't and the other way around.…”

Section: Machine Learning Techniques For Data Mining: a Surveymentioning

confidence: 99%

“…This paper presents different arrangement strategies. In any field one classification technique is more helpful than another [3].…”

Section: Machine Learning Techniques For Data Mining: a Surveymentioning

confidence: 99%

Analytical Study of Image Classsification Using Deep Learning

yousuf

2018

ijarcs

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Abstract:The machine learning technology has received increased attention in recent years in several vision tasks such as image classification, image detection, and image recognition. In particular, recent advances of machine learning techniques bring encouragement to image classification with convolutional neural networks. CNN has been established as a powerful class of models for image recognition problems and even in some cases they outperform humans. The main purpose of the work presented in this paper is the rise and development of machine learning, deep learning, CNN and to give an overview on using machine learning for image classification. At the end the comparison of CNN with traditional method is discussed.

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“…This technique provides intelligence decision making and it is used not only for studying and investigating the current instance, but also predicting the future behavior of same instance. Classification includes two phases: first, in the training phase the dataset is analyzed and in the second phase, the data is tested and the accuracy of the classification algorithm is achieved (Sharma et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Data mining and machine learning: an Overview of Classifiers

Haghighi¹

2015

CeN

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At the same time of information age, digital revolution has made necessary using some of technologies to analyze most of essential information. Data mining is a technique to make sense to the available data. The aim of data mining is extracting the information from a vast volume of data and transforming them into a comprehensible form for human. For this purpose, machine learning methods are used to classify data.In this study, we discuss six popular and useful classifiers in the data mining process.

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Machine learning techniques for data mining: A survey

Cited by 57 publications

References 14 publications

Applying methods of machine learning in the task of intrusion detection based on the analysis of industrial process state and ICS networking

Applying methods of machine learning in the task of intrusion detection based on the analysis of industrial process state and ICS networking

Analytical Study of Image Classsification Using Deep Learning

Data mining and machine learning: an Overview of Classifiers

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