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In medical science, sleep stages are the main criteria to define the disorders and have crucial role on diagnostic. In this sense, accurate sleep stage classification plays important role due to provide better report on medications and diagnoses. In this study, EEG signals are classified by a rule based machine learning algorithm; Decision Tree with the ensemble and classical machine learning idea...
Authors can be differentiated by their styles of writing. In this paper, we propose features which attempt to classify authors based on their writing styles. The features can be usage of parts of speech, punctuation marks, word lengths, sentence lengths, number of unique words used, etc. This concept is used in many fields like email classification, fraud detection, etc. We propose a module to extract...
An intelligent system uses machine learning algorithms to provide outputs to every input provided. The introduction of emotions in intelligent systems is required to create systems that are more similar to human beings and thus more reliable. In this paper, the idea of introducing the emotion ‘uncertainty’ in Intelligent Systems is proposed. A Semi-Automated Intelligent System is introduced in this...
The electroencephalography (EEG) data records vast amounts of human cerebral activity yet is still reviewed primarily by human readers. Most of the times, the data is contaminated with non-cerebral originated signals, called artifacts, which could be very difficult to visually detect and, undiscovered, could damage the neural information analysis. The purpose of our work is to detect the artifacts...
We present an optimization technique for general object detection and an algorithm for training decision trees. By delaying the calculation of the features as late as possible we drastically reduce the execution time. At detection we alternate between evaluating the necessary features and eliminating candidates. This enables us to have both a rich pool of features and a powerful classifier while keeping...
The continuing success of synchrophasors has ushered in new subdomains of power system applications for real-time situational awareness, online decision support, and robust system control. In this paper, an adaptive decision-tree-based systematic method for open-loop regional voltage control is developed. This approach employs voltage security assessment method to generate voltage secure and insecure...
Graduate employability is an increasingly major concern for academic institutions and assessing student employability provides a way of linking student skills and employer business requirements. Enhancing student assessment methods for employability can improve their understanding about companies in order to get suitable company for them. So, enhanced employability prediction of student can help them...
This paper focuses on the problem of machine learning classifier choice for network intrusion detection, taking into consideration several ensemble classifiers from the supervised learning category. We have evaluated Bagged trees, AdaBoost, RUSBoost, LogitBoost and GentleBoost algorithms, provided an analysis of the performance of the classifiers and compared their learning capabilities, taking for...
Flight parameters record the flight state and performance of the each flight phase. The precise division of the aircraft flight process using flight parameters can not only perform the stage quality evaluation of the whole flight process, but also can detect the aircraft faults. In this paper, the decision tree classifier is used to divide the flight parameters. The parameter reduction is carried...
The design of effective financial early warning algorithm is of great significance to the financial management of the company. The weak classification algorithm can be improved to a high classification algorithm with high recognition rate through the ensemble learning. The algorithm can overcome the drawback of low classification accuracy of single classifier. Therefore, this paper combines decision...
This paper proposes a method for construction of classifiers for discharge summaries. First, morphological analysis is applied to a set of summaries and a term matrix is generated. Second, correspond analysis is applied to the classification labels and the term matrixand generates two dimensional coordinates. By measuring thedistance between categories and the assigned points, ranking of key wordswill...
The goals of this paper were twofold: to continue and refine previous research in the topic of tree cover type classification by harnessing modern machine learning models, and to extend the conclusions of that work to demonstrate that results gained from such models can be used to assist U.S. land management agencies in current challenges they face. Using the same dataset as the past study, an artificial...
This paper suggests identification and classification of fault at the time of power swing by using decision tree approach for transmission system network. The power swing which occurs during switching in/out of heavy loads, after fault clearance condition etc causes change in active and reactive power. The suggested decision tree method initially retrieves the information about fault/ power swing...
Vehicle detection is the core function in any Driver Assistant System. Besides the challenge in various environmental conditions, the limitation in execution time and computing power is also critical. This paper proposes a shadow detection step that aims at recognizing the shadow part of the train in various environments (including very tough cases) to accelerate the detection process. We propose...
Twitter is one of world most famous social media. There are many statement expresed in Twitter like happiness, sadness, public information, etc. Unfortunately, people may got angry to each other and write it down as a tweet on Twitter. Some tweet may contain Indonesian swear words. It's serious problem because many Indonesians may not tolerated swear words. Some Indonesian swear words may have multiple...
Fully automated defect detection and classification of automobile components are crucial for solving quality and efficiency problems for automotive manufacturers, due to the rising wage, production costs and warranty claims. However, metrological deviations in form still represent unsolved problems using state-of-the-art techniques, especially for forged or casted components with complex geometry...
In recent years due to increased competition between companies in the services sector, predict churn customer in order to retain customers is so important. The impact of brand loyalty and customer churn in an organization as well as the difficulty of attracting a new customer per lost customer is very painful for organizations. Obtaining a predictive model customer behaviour to plan for and deal with...
Intrusion Detection Systems (IDSs) are powerful systems which monitor and analyze events in order to detect signs of security problems and take action to stop intrusions. In this paper, the Two Layers Multi-class Detection (TLMD) method used together with the C5.0 method and the Naive Bayes algorithm is proposed for adaptive network intrusion detection, which improves the detection rate as well as...
In the big data era, machine learning has become an increasingly popular approach for data processing. Data could be in various forms, such as text, images, audios, videos and signals. The essence of machine learning is to learn any patterns from features of data. In the above types of data, the number of features is massively high, which could result in the presence of a large number of irrelevant...
Action recognition in videos is a hot research topic in computer vision because of the popularization of application such as human-machine interaction, intelligent monitoring. Recently, with the aging phenomenon of population becoming more and more serious, the analysis of senior actions is becoming more and more important. Random forest has been wildly used in action recognition because of its efficiency...
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