CART

یکی از مشکلات بزرگ نظام آموزش و پرورش و خانوادههای دارای فرزند که هر سال منجر به هدر رفتن میزان زیادی از امکانات، منابع و
استعدادهای بالقوه انسانی میشود و تأثیرات غیرقابل جبرانی را در ابعاد فردی و اجتماعی به جای میگذارد، پدیدهی افت تحصیلی است. بنابراین
نظام آموزش و خانوادهها باید به دنبال راه حلی برای به حداقل رساندن این خسارتها باشند. این مقاله با شناسایی عوامل موثر بر افت تحصیلی با
استفاده از دادهکاوی آموزشی، تلاش میکند تا با معرفی این عوامل مشکلساز به مسوولین آموزشی از وقوع این پدیده جلوگیری شود. در این
به اطلاعات جمعآوری شده از دانش آموزان سال اول یکی CART و درخت تصمیم K-Means پژوهش پس از اعمال الگوریتمهای خوشه بندی
از دبیرستانهای شهر یزد، مهمترین عوامل موثر بر وقوع افت تحصیلی استخراج شدند.

Abstract: Data Mining is a very interesting area to mine the data for knowledge. Several techniques are available. A data mining is one of the fast growing research field which is used in a wide areas of applications. The data mining consists of classification algorithms, association algorithms and searching algorithms. We are using clustering and decision tree methods to mine the data by using hybrid algorithms K-means, SOM and HAC algorithms from clustering and ID3 and C4.5 and CART algorithms from decision tree and it can produce the better results than the traditional algorithms. The comparative study of these algorithms to obtain which one is high accuracy, frequency, measure, procedure, Pruning, error rate and time complexities from the decision tree algorithm. At the same time the comparative study of these algorithms to obtain which one is quality, error rate, computation time, accessing time, performance, number of cluster, Map topology, type of software, type of data, and data set size from the clustering algorithm.
Key words: K-MEANS, SOM, HAC, ID3, C4.5, CART
Title: Comparative Study of different clustering and Decision Tree for Data Mining Algorithm
Author: Ms. A. Sivasankari,  Mrs. S. Sudarvizhi, S. Radhika Amirtha Bai
International Journal of Computer Science and Information Technology Research
ISSN 2348-120X (online), ISSN 2348-1196 (print)
Research Publish Journals

دانشآموزان مختلف همواره از سطوح یادگیری متفاوتی برای درسهای خود برخوردار هستند. به عبارت دیگر، این گونه نیست که دانشآموزی
با معدل کل پایین، از ضعف یکسانی در یادگیری همهی دروس خود رنج ببرد. با توجه به اینکه مدارس کشور دادهها و اطلاعات زیادی از نمرات
دانشآموزان را ثبت میکنند، به نظر میرسد که در اکثر مواقع این دادهها میتوانند حامل اطلاعات و الگوهای باارزشی باشند. دادهکاوی در
حقیقت کشف دانش و الگوهای پنهان در مجموعه دادهها با استفاده از الگوریتمهای خاص میباشد. در مقالهی پیش رو، سعی بر این بوده است که
با اعمال تکنیکهای دادهکاوی بر روی نمرات دانشآموزان سال اول دبیرستان مهدیه شهر یزد، دستهبندی مناسبی برای این دانشآموزان ارائه داده
شود. نتایج حاصل از این تحقیق میتواند در جهت ارتقاء و بهبود فرآیندهای آموزشی نظیر برنامهریزی، ثبت نام، ارزیابی و مشاوره از سوی
مسوولین آموزشی به کار گرفته شود.

Credit scoring is a procedure that exists in every financial institution. A way to predict whether the debtor was qualified to be given the loan or not and has been a major concern in the overall steps of the loan process. Almost all banks and other financial institutions have their own credit scoring methods. Nowadays, data mining approach has been accepted to be one of the well-known methods. Certainly, accuracy was also a major issue in this approach. This research proposed a hybrid method using CART algorithm and Binary Particle Swarm Optimization. Performance indicators that are used in this research are classification accuracy, error rate, sensitivity, specificity, and precision. Experimental results based on the public dataset showed that the proposed method accuracy is 78 % and 87.53 %. In compare to several popular algorithms, such as neural network, logistic regression and support vector machine, the proposed method showed an outstanding performance.

The purpose of this study is to describe the personal hygiene and sanitation of food cutlery (bowl) on meatball cart traders at Makassar City. This research using descriptive observational with non-probability sampling techniques and accidental sampling method. 80% respondents had good personal hygiene. Almost all respondents qualify the requirement of hand and finger hygiene, as well as hair hygiene. For clothes hygiene indicators, most qualify the requirements. As for the indicators of handwashing practices and the use of gloves, all respondents did not qualify the requirements. While the results of research related to food cutlery sanitation showed that knowledge that 86.7% were high, but many still did not know washing water requirements and bowl conditions when in storage. Most handlers attitude was categorized as adequate. It is suggested that the meatball cart traders always pay attention to hand hygiene and sanitation of cutlery to avoid bacterial contamination.

Market basket analysis is one of the techniques of knowledge mining used in a broad dataset or database to find a collection of items that are interwoven. Generally used in a sale, the most relevant shopping cart data is used. This methodology has been widely applied in different multinational or foreign industries and is very useful in consumer buying preferences. Technology advances change business trends dramatically, shifting customer demands require increased surgical accuracy of business. In this research, the writer wants to analyze the shopping cart using apriori algorithm, with a dataset from the Kaggle web. Using anaconda software features with the Python programming language is expected to create knowledge overwriting consumer buying patterns. In conclusion, this pattern can be used to support industry in managing its company activities.

Background Data on combination antiretroviral therapy (cART) in remote rural African regions is increasing. Methods We assessed prospectively initial cART in HIV-infected adults treated from 2005 to 2008 at St. Francis Designated District Hospital, Ifakara, Tanzania. Adherence was assisted by personal adherence supporters. We estimated risk factors of death or loss to follow-up by Cox regression during the first 12 months of cART. Results Overall, 1,463 individuals initiated cART, which was nevirapine-based in 84.6%. The median age was 40 years (IQR 34-47), 35.4% were males, 7.6% had proven tuberculosis. Median CD4 cell count was 131 cells/μl and 24.8% had WHO stage 4. Median CD4 cell count increased by 61 and 130 cells/μl after 6 and 12 months, respectively. 215 (14.7%) patients modified their treatment, mostly due to toxicity (56%), in particular polyneuropathy and anemia. Overall, 129 patients died (8.8%) and 189 (12.9%) were lost to follow-up. In a multivariate analysis, low CD4...

Over the last few years, connectionism or neural networks (NN) have successfully been applied to a wide range of areas and have demonstrated their capabilities in solving complex problems. Current indications show that these techniques are very important and rapidly developing areas of research and applications, particularly, in the area of data mining for knowledge discovery. One particular neural network model, the back-propa-gation (BP) algorithm, has performed very well in this regard and it is now accepted as a reliable method for data mining. However, these models have their shortcomings. The major difficulty lies in the fact that the relationships between specific variables and the neural network results are, at best, difficult to explain. This article presents an innovative but simple method for using NN to understand the pattern/outcome correlation to inter-pret a cause and effect relationship. A comparative analysis and experimental results are also presented to show the v...

Combined antiretroviral therapy (cART) in HIV-infected patients has been associated with lipodystrophy, metabolic abnormalities, and an increased risk of cardiovascular disease. Ultrasound measures of carotid artery intima-media thickness (cIMT) have been used as a valid measure of subclinical atherosclerosis and as a tool to predict the risk of cardiovascular events. Our aim was to evaluate the progression of cIMT in HIV-infected patients subjected to cART, with and without lipodystrophy, over a one-year period. We performed a one-year prospective cohort study to compare changes in cIMT, metabolic and inflammation markers in HIV-infected patients undergoing cART. Body composition was assessed by dual-energy X-ray absorptiometry (DXA) and abdominal computed tomography (CT). Levels of blood pressure, lipids and inflammatory markers were evaluated, as well as ultrasound measures of cIMT. Lipodystrophy defined by Fat Mass Ratio (L-FMR) is measured as the ratio of the percentage of trun...

Over the last few years, connectionism or neural networks (NN) have successfully been applied to a wide range of areas and have demonstrated their capabilities in solving complex problems. Current indications show that these techniques are very important and rapidly developing areas of research and applications, particularly, in the area of data mining for knowledge discovery. One particular neural network model, the back-propagation (BP) algorithm, has performed very well in this regard and it is now accepted as a reliable method for data mining. However, these models have their shortcomings. The major difficulty lies in the fact that the relationships between specific variables and the neural network results are, at best, difficult to explain. This article presents an innovative but simple method for using NN to understand the pattern/outcome correlation to interpret a cause and effect relationship. A comparative analysis and experimental results are also presented to show the val...

Introduction Despite its effectiveness, the optimal use of the combination of insecticide treated nets (ITN) and intermittent preventive treatment during pregnancy with sulfadoxine-pyrimethamine (TPIg-SP) remains low in malaria endemic areas. Therefore, we studied its variations and predictors in Guinea.MethodsWe conducted a secondary analysis of the 2012 and 2018 Guinea Demographic and Health Surveys (DHS). It included women who had given birth in the 3 years before each DHS, slept on ITN and took at least one dose of SP. Moran indices were used to determine spatial autocorrelation. A logistic regression and classification and regression tree (CART) identified the predictors of malaria preventive measures (MPM).ResultsIn 2012, 60.88% of pregnant women used MPM incompletely compared with 79.11% in 2018. Associated factors with incomplete MPM in 2012 were as follows: having an indirect link with the head of household (AOR = 2.23, 95% CI 1.08–4.61) and performing at least 4 ANCs (AOR ...

Air temperature is an essential climatic component particularly in water resources management and other agro-hydrological/meteorological activities planning This paper examines the prediction capability of three machine learning models, least square support vector machine (LSSVM), group method and data handling neural network (GMDHNN) and classification and regression trees (CART) in air temperature forecasting using monthly temperature data of Astore and gilgit climatic stations of Pakistan. The prediction capability of three machine learning models is evaluated using different time lags input combinations with help of root mean square error (RMSE), the mean absolute error (MAE) and coefficient of determination (R2) statistical indicators. The obtained results indicated that the LSSVM model is more accurate in temperature forecasting than GMDHNN and CART models. LSSVM significantly decreases the mean RMSE of the GMHNN and CART models by 1.47-3.12% and 20.01-25.12% for the Chakdara and Kalam Stations, respectively.

HIV-infected migrants were shown to have poorer treatment outcomes than Dutch HIV-infected patients, often due to worse treatment adherence. Self-reported adherence would be an easy way to monitor adherence, but its validity relative to pharmacy refill adherence has not been extensively evaluated in migrants. All HIV-infected migrants older than 18 years and in care at the two Rotterdam HIV-treatment centers were eligible. Refill data with leftover medication (PRL) (residual pill count) were obtained from their pharmacies up to 15 months prior to inclusion. Self-reported adherence to combination Antiretroviral Therapy was assessed by four questions about adherence at inclusion. Additionally, risk factors for pharmacy refill non-adherence were examined. In total, 299 HIV-infected migrants were included. Viral load (VL) was detectable in 11% of the patients. Specificity of PRL was 53% for patients with an adherence of 100% and decreased with lower cut-off values. Sensitivity and negat...

In this paper, new computational intelligence sequential hybrid architectures involving Genetic Programming (GP) and Group Method of Data Handling (GMDH) viz. GP-GMDH. Three linear ensembles based on (i) arithmetic mean (ii) geometric mean and (iii) harmonic mean are also developed. We also performed GP based feature selection. The efficacy of Multiple Linear Regression (MLR),

This dissertation proposes content based image classification and retrieval with Classification and Regression Tree (CART). A simple CBIR system (WH) is designed and proved to be efficient even in the presence of distorted and noisy images. WH exhibits good performance in terms of precision, without using any intensive image processing feature extraction techniques. Unique indexed color histogram and wavelet decomposition based horizontal, vertical and diagonal image attributes have been chosen as the primary attributes in the design of the retrieval system. The output feature vectors of the WH method serve as input to the proposed decision tree based image classification and retrieval system. The performance of the proposed content based image classification and retrieval system is evaluated with the standard SIMPLIcity dataset which has been used in several previous works. The performance of the system is measured with precision as the metric. Holdout validation and k-fold cross v...