نتایج جستجو برای: decision tree
تعداد نتایج: 495245 فیلتر نتایج به سال:
One of the most common causes or credit phenomenon that is taken into account for credit risk is the customer’s noncompliance with the commitments. Thus, by predicting the behavior of loan applicants, the growth rate of debts can be decreased. Hence, this study is conducted on corporate applicants for loans in one of the public banks in Iran. In this paper, the main elements comprising the cus...
Efficiency is an issue of importance and interest to both managers of different organizations and customers who use the products and services of these organizations. The aim of this research is to study the efficiency of pharmaceutical companies accepted in the Stock Exchange Organization by using Window Data Envelopment Analysis (WDEA) and then, to provide some rules based on the decision tree...
Background and Aim: Neonatal jaundice is a matter that is very important for clinicians all over the world because this disease is one of the most common cases that requires clinical care. The aim of this study is to use data classification algorithms to predict the type of jaundice in neonates, and therefore, to prevent irreparable damages in future. Materials and Methods: This is a descripti...
we used various screening techniques, clustering, decision tree and generalized rule induction (association) (gri) models and molecular phylogenic relationship to search for patterns of halophi-licy and to find features contribute to halolysin salt stability. we found met was the sole n-terminal amino acid in halolysin proteins, whereas other amino acids found at this position of oth-er proteas...
Background and Objective: Unwanted pregnancy is a pregnancy that is considered to be unwanted by at least one member of the couple, and has adverse consequences for the family and community. Using four classification models, this study predicted unwanted pregnancy in the urban population of Khorramabad and compared these classification models. Materials and methods: In this cross-sectional s...
Decision-tree algorithms provide one of the most popular methodologies for symbolic knowledge acquisition. The resulting knowledge, a symbolic decision tree along with a simple inference mechanism, has been praised for comprehensibility. The most comprehensible decision trees have been designed for perfect symbolic data. Classical crisp decision trees (DT) are widely applied to classification t...
Most of the methods that generate decision trees for a specific problem use examples of data instances in the decision tree generation process. This paper proposes a method called “RBDT-1”rule based decision tree -for learning a decision tree from a set of decision rules that cover the data instances rather than from the data instances themselves. RBDT-1 method uses a set of declarative rules a...
as we know that with the help of Data mining techniques we can find out knowledge in terms of various characteristics and patterns. In this regard this paper presents finding out of anomalies/ outliers using various decision tree based classifiers viz. Best-first Decision Tree, Functional Tree, Logistic Model Tree, J48 and Random Forest decision tree. Three real world datasets has been used in ...
Background: Diabetes mellitus has several complications. The Late diagnosis of diabetes in people leads to the spread of complications. Therefore, this study has been done to determine the possibility of predicting diabetes type 2 by using data mining techniques. Methods: This is a descriptive-analytic study that was conducted as a cross-sectional study. The study population included people re...
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