نتایج جستجو برای: combined with the hybrid feature selection method
تعداد نتایج: 18094643 فیلتر نتایج به سال:
Feature Selection (FS) is an important pre-processing step in machine learning and data mining. All the traditional feature selection methods assume that the entire feature space is available from the beginning. However, online streaming features (OSF) are an integral part of many real-world applications. In OSF, the number of training examples is fixed while the number of features grows with t...
Increasing the use of Internet and some phenomena such as sensor networks has led to an unnecessary increasing the volume of information. Though it has many benefits, it causes problems such as storage space requirements and better processors, as well as data refinement to remove unnecessary data. Data reduction methods provide ways to select useful data from a large amount of duplicate, incomp...
This paper proposes a hybrid method to find cumulative distribution function (CDF) of completion time of GERT-type networks (GTN) which have no loop and have only exclusive-or nodes. Proposed method is cre-ated by combining an analytical transformation with Gaussian quadrature formula. Also the combined crude Monte Carlo simulation and combined conditional Monte Carlo simulation are developed a...
The manipulation of large-scale document data sets often involves the processing of a wealth of features that correspond with the available terms in the document space. The employment of all these features in the learning machine of interest is time consuming and at times reduces the performance of the learning machine. The feature space may consist of many redundant or non-discriminant feature...
Feature selection refers to the problem of selecting relevant features which produce the most predictive outcome. In particular, feature selection task is involved in datasets containing huge number of features. Rough set theory has been one of the most successful methods used for feature selection. However, this method is still not able to find optimal subsets. This paper proposes a new featur...
This study proposes an alternate data extraction method that combines three well-known feature selection methods for handling large and problematic datasets: the correlation-based (CFS), best first search (BFS), dominance-based rough set approach (DRSA) methods. aims to enhance classifier’s performance in decision analysis by eliminating uncorrelated inconsistent values. The proposed method, na...
Machine learning has been expansively examined with data classification as the most popularly researched subject. The accurateness of prediction is impacted by provided to algorithm. Meanwhile, utilizing a large amount may incur costs especially in collection and preprocessing. Studies on feature selection were mainly establish techniques that can decrease number utilized features (attributes) ...
abstract amino acids are building blocks of proteins, and play a vital role in living beings existence and their functionality. the interaction of these compounds with metal ions is of great importance to biochemists, and chemists, because their functions can be utilized as a model in understanding enzymes mechanism for transport of metal ions to tissues. among twenty essential amino acids w...
Clustering is the most common form of unsupervised learning.In clustering, it is the distribution and makeup of the data that will determine cluster membership. It needs representation of objects and similarity measure. which compares distribution of features between objects. For the high dimensionality, feature extraction and feature selection improves the performance of clustering algorithms....
The imbalance data can be seen in various areas such as text classification, credit card fraud detection, risk management, web page classification, image classification, medical diagnosis/monitoring, and biological data analysis. The classification algorithms have more tendencies to the large class and might even deal with the minority class data as the outlier data. The text data is one of t...
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