Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different cancer types is important for cancer diagnosis and drug discovery, SGD-SVM is applied for classifying the most common leukemia cancer type dataset. The results that are gotten using SGD-SVM are much accurate than other results of many studies that used the same leukemia datasets.
The aim of this study is for testing the applicability of Ramamoorthy and Murphy method for identification of predominant pore fluid type, in Middle Eastern carbonate reservoir, by analyzing the dynamic elastic properties derived from the sonic log. and involving the results of Souder, for testing the same method in chalk reservoir in the North Sea region. Mishrif formation in Garraf oilfield in southern Iraq was handled in this study, utilizing a slightly-deviated well data, these data include open-hole full-set logs, where, the sonic log composed of shear and compression modes, and geologic description to check the results. The Geolog software is used to make the conventional interpretation of porosity, lithology, and saturation. Also,
... Show MoreThe recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach
... Show MoreThis paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).
In this research was the study of a single method of estimation and testing parameters mediating variables (Mediation) in a specimen structural equations SEM a bootstrap method, for the purpose of application of the integrated survey of the situation Marital data and health mirror Iraqi (I-WISH) for the year 2011 from the Ministry of Planning - device Central Bureau of Statistics, and applied to the appropriate data from the terms of the data to a form of structural equation SEM using factor analysis affirmative (Confirmatory Factor analysis) CFA As a way to see the match variables that make up the model, and after confirming the model matching or suitability are having the effect of variables mediation in the model tested by the
... Show MoreA stochastic process {Xk, k = 1, 2, ...} is a doubly geometric stochastic process if there exists the ratio (a > 0) and the positive function (h(k) > 0), so that {α 1 h-k }; k ak X k = 1, 2, ... is a generalization of a geometric stochastic process. This process is stochastically monotone and can be used to model a point process with multiple trends. In this paper, we use nonparametric methods to investigate statistical inference for doubly geometric stochastic processes. A graphical technique for determining whether a process is in agreement with a doubly geometric stochastic process is proposed. Further, we can estimate the parameters a, b, μ and σ2 of the doubly geometric stochastic process by using the least squares estimate for Xk a
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The great scientific progress has led to widespread Information as information accumulates in large databases is important in trying to revise and compile this vast amount of data and, where its purpose to extract hidden information or classified data under their relations with each other in order to take advantage of them for technical purposes.
And work with data mining (DM) is appropriate in this area because of the importance of research in the (K-Means) algorithm for clustering data in fact applied with effect can be observed in variables by changing the sample size (n) and the number of clusters (K)
... Show Moreإسهام تطبيقات التكنولوجيا الرقمية في تطوير الكفاءات النحوية لطلبة اللغة الإسبانية في العراق.
In linear regression, an outlier is an observation with large residual. In other words, it is an observation whose dependent-variable value is unusual given its values on the predictor variables. An outlier observation may indicate a data entry error or other problem.
An observation with an extreme value on a predictor variable is a point with high leverage. Leverage is a measure of how far an independent variable deviates from its mean. These leverage points can have an effect on the estimate of regression coefficients.
Robust estimation for regression parameters deals with cases that have very high leverage, and cases that are outliers. Robust estimation is essentially a
... Show MoreThis study includes the application of non-parametric methods in estimating the conditional survival function of the Beran method using both the Nadaraya-Waston and the Priestley-chao weights and using data for Interval censored and Right censored of breast cancer and two types of treatment, Chemotherapy and radiation therapy Considering age is continuous variable, through using (MATLAB) use of the (MSE) To compare weights The results showed a superior weight (Nadaraya-Waston) in estimating the survival function and condition of Both for chemotherapy and radiation therapy.