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One of the challenges of data mining is finding hyperparameters for a learning algorithm that will produce the best model for a given dataset. Hyperparameter optimization automates this process, but it can still take significant time. It has been found that hyperparameter optimization does not always result in induced models with significant improvement over default values, yet no systematic analysis...
Fingerprinting Localization Solutions (FPSs) enjoy huge popularity due to their good performance and minimal environment information requirement. Considered as a data-driven approach, many modern data analytics can be used to improve its performance. In this paper, we propose tow learning algorithms, namely a deep learning architecture for regression and Support Vector Machine (SVM) for classification,...
Electroencephalography (EEG) is a technique for the acquisition of electrical brain signals. In recent years the increase of information acquired from signal analysis has genereted a large amount of data; therefore, the development of tools for analysis has become necessary. In this paper, the mEEG prototype for EEG data managing is presented. It offers a user-friendly communication solution to exchange...
Over the past few years, several approaches have been proposed to assist in the early diagnosis of Alzheimer's disease (AD) and its prodromal stage of mild cognitive impairment (MCI). For solving this high dimensional classification problem, the widely used algorithm remains to be Support Vector Machines (SVM). But due to the high variance of the data, the classification performance of SVM remains...
In this modern era of communication, people are always connected to the internet. Hence, everyone tends to express their opinions on social media or e-commerce websites about commercial products, movies, sports, social and geopolitical matters and even on government policies. These opinions reflect the corresponding person's view or sentiment about that particular matter, which ultimately leads to...
Web spam is a big problem for search engine users in World Wide Web. They use deceptive techniques to achieve high rankings. Although many researchers have presented the different approach for classification and web spam detection still it is an open issue in computer science. Analyzing and evaluating these websites can be an effective step for discovering and categorizing the features of these websites...
DDoS attacks bring huge threaten to network, how to effectively detect DDoS is a hot topic of information security. Currently, there are some methods designed to detect DDoS attacks, but the detection rate of them is low. Moreover, DDoS detection is easily misled by flash crowd traffic. In this paper, a new method to detect DDoS attacks based on RDF-SVM algorithm is proposed. By considering the importance...
At present, shallow characteristics are usually utilized to represent the distributed features of text for Chinese spam classification, causing the problem of inexact text vector representation and low classification performance. A novel Chinese spam classification method based on weighted distributed feature is proposed by combining the features of TF-IDF weighted algorithm with the distributed text-based...
For face recognition systems, impostors can obtain legal identity authentication by presenting the printed images, the downloaded images or candid videos to the sensor. In this paper, an enhanced face local binary feature (ELBP) of a face map is extracted as a classification feature to identify whether the face map is a real face or a fake face. Compared with the dynamic or static methods proposed...
Infertility is the inability pregnant in one year. The incidence of infertility is increasing day by day. Spermiogram (sperm test) is non-invasive and infertility is diagnosed with this test. The treatment is based on the result of the test. In this study, computer assisted sperm analysis (CASA) was performed on sperm images using image processing algorithms.
A hybrid least square support vector machine (LSSVM) is proposed to predict the boiler combustion efficiency. In this approach, a principal component analysis (PCA) is employed to reconstruct new variables as the input of the predictive model. Then, a particle swarm optimization (PSO) algorithm optimized LSSVM is proposed. The parameters of LSSVM are optimized dynamically by PSO and the output value...
Musical instruments are consist of wide variety of domain so manual classification of these instruments is difficult and challenging task. To make the process of classifying musical instrument easy and less dependent on human supervision given system is designed. There are some algorithm are available for classification tsk from which we uses SVM, MLP and AdaBoost for better result. This system mainly...
In this paper, the operating conditions of vehicle internal combustion engine (ICE) waste heat utilization system are monitored by improved support vector machines (SVMs). Organic Rankine Cycle (ORC) is used to recover the ICE waste heat. Several optimal approaches are employed when training SVMs. The improved SVMs are then employed to monitor the operating conditions of the ICE waste heat recovery...
Advances in highly multi-parametric measurements by mass cytometry have made possible the accurate detection of acute myeloid leukemia (AML) cells in complex cell populations. However, current informatics methods bottlenecks data processing by being labor-intensive, time-consuming, and prone to user bias. To address these problems, major efforts have been made to automate the detection of AML cells...
The interoperability testing of CTCS-3 Level Train Control System guarantees the safe operation of train running on different lines. It makes great sense to achieve automatic analysis of interoperability testing results, which could improve the efficiency and accuracy of testing. In this paper, a research was conducted on automatic analysis of testing results for on-board equipment of train control...
Sensor plays an important role in complex industrial environment. Therefore, researches on sensor fault diagnosis technology are important for improving the reliability of industry system. A sensor signal which is non-linear and non-stationary, has many kinds of structural characteristics and sensing properties. On the basis of supervised locally linear embedding (SLLE), support vector machine (SVM),...
In water flooding oilfield, petroleum production is the most crucial target for production-injection wells system. An effective, informative and accurate production prediction facilitates parameter adjustment, production optimization, fault analysis and decrease in production cost. Some effective Artificial Intelligence (AI) technologies have been widely used in various kinds of industrial fields...
Unlike most researches focus on computation reduction, the fast algorithm proposed in this paper aims at maintaining the coding efficiency as high as possible. In the proposed algorithm we employ support vector machine (SVM) that uses three parameters as features: variances, low-frequency AC components of DCT and spatially neighboring CU levels for fast CU size decision. In addition, based upon RMD...
The paper describes the study on the problem of applying classification techniques in medical datasets with a class imbalance. The aim of the research is to identify factors that negatively affect classification results and propose actions that may be taken to improve the performance. To alleviate the impact of uneven and complex class distribution, methods of balancing the datasets are proposed and...
We propose a method for semi-supervised classification using a combination of ensemble clustering and kernel based learning. The method works in two steps. In the first step, a number of variants of clustering partition are obtained with some clustering algorithm working on both labeled and unlabeled data. Weighted averaged co-association matrix is calculated using the results of partitioning. We...
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