Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa

<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c

Linear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear  classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.

In this paper we have been focus for the comparison between three forms for classification data belongs

The most important contemporary issues which related to the survey of the influence of communication development technology to land use sustainability. The research aims to explain the changes that happened in the quality & land use activities performance by understanding the transformations due to modern technology and its impact on current uses and its impact on changing functional relationships between those uses to create new combinations or hybrid uses.Research will follow the analytical descriptive approach in presenting the problem of research. Research has several conclusions & recommendations, one of conclusions is the change of the place concept and its relation to changing the concept of land use and its sustai

The land cover of Mahmudiyah city, located south of the capital, Baghdad - Iraq, was studied for the period from 1986 to 2021 with five years between every two successive scenes, where Landsat scenes were used downloaded from the US Geological Survey (USGS ) website with low cloud cover for sensors TM and OLI. The land cover of the study area was classified. The total accuracy of the classification was calculated, as well as the analysis of the user accuracy and the classifier accuracy (maximum likelihood) and its impact on the overall classification accuracy. The lowest accuracy value in 2009 was (85.101% (and the highest accuracy value in 1995) was 95.654%). The constancy percentage of the class for the adopted years was calculated and

Sawa Lake is one of the unique lakes in Iraq. It is located in the southwestern part of Iraq. It is one of the closed lakes, as no surface water source works to feed the lake. The lake feeds on groundwater. The source of this groundwater is the Dammam Basin. During the past ten years, The lake has had many changes, which led to a decrease in water levels. This also led attention to study of the causes of these changes. Many types of research were presented in the study of the state of the lake. This research used remote sensing images from Landsat 8 OLI to monitor the changes during 2020-2021 by applying the NDWI equation to extract water area from image data. The results of the areas were obtained from a special report by Normalized Dif

Sea level rise (SLR) due to climate change is affecting the coastline, causing shoreline changes, the degradation of mangrove forests, and the destruction of coastal resources. This is the cause of a huge amount of mangrove degradation in many parts of the Ganges–Brahmaputra–Meghna delta. A total of 90% of people have been forced to migrate from the island due to extreme weather conditions. In this study, remote sensing (RS) and geographic information system (GIS) techniques were used for LULC change and shoreline shift analyses of Ghoramara Island. LULC classification was carried out using thirty years of Landsat datasets with intervals of ten years (1990 and 2000) and intervals of five years (2005, 2010, 2015, and 2020). The classific