[PDF] Top 20 A Hybrid Classification Model For Diabetes Dataset Using Decision Tree
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A Hybrid Classification Model For Diabetes Dataset Using Decision Tree
... JETIR1508008 Journal of Emerging Technologies and Innovative Research (JETIR) www.jetir.org 3306 x_{2,i}, ...,x_{p,i}) , where the x_j represent attributes or features of the sample, as well as the class in which s_i ... See full document
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A hybrid classification model employing genetic algorithm and root guided decision tree for improved categorization of data
... measure. Classification techniques fall under the supervised learning technique and has been widely used for the purpose of data ...analysis. Decision trees are one of the most effective ways for ... See full document
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Identification of Models Decision Tree and Random Forest Classifier using Rattle on Diabetes Disease
... Abstract— Diabetes is the disease which is growing now a days in human body and there are a number of patient who are suffering by this diabetes in the ...researchers using this type of ...the ... See full document
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Machine Learning Approach for Intrusion Detection on Cloud Virtual Machines
... NB Tree[11,12], and Random forest[13] for virtual ...NB Tree algorithm is used to classify network connections into intrusion and normal data based on a labeled training dataset that helps it in ... See full document
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Comparison Of Datamining Techniques For Prediction Of Breast Cancer
... three model Naive Bayes is indicated as the best ...selected using Information Gain and ...disease using classification ...patient’s using data mining ...the dataset. ... See full document
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A Framework for Child Development analysis and Learning Disability Prediction using a Hybrid Naive Bayes and Decision Tree Fusion Technique – NB Tree
... A major idea of machine learning research is to automatically learn to recognize complex patterns and make intelligent decisions based on data. In recent years the sizes of databases have increased rapidly. This has lead ... See full document
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Designing Spam Model Classification Analysis using Decision Trees
... spam model using classification technique in data ...spam dataset downloaded from the UCI machine learning repository which was classified using a popular data mining tool called ... See full document
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A Novel Decision Tree Algorithm for Land Cover Classification Using Hybrid Polarimetric Sar Data
... for decision tree classification shows promising results for different features such as odd, even and volume ...scatterers.The decision treeclassifier detects all land cover features more ... See full document
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Comparison of Classification Techniques For Diabetes Dataset Using Weka Tool
... RANDOM tree and REP tree. By using these techniques we trained out results on the basis of time taken to build model, correctly classified instances, error and ROC ... See full document
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Hybrid Decision Tree and Naïve Bayes Classifier for Predicting Study Period and Predicate of Student’s Graduation
... Decision tree is a very powerful and well-known classification ...The decision tree method transforms a fact into a decision tree that represents the ...rule. ... See full document
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Classification Model Using Optimization Technique: A Review
... In Classification of Data Mining, There are analyzing different kind of data mining techniques introduced in recent years for ...the Classification over different ...different dataset using ... See full document
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Diabetes Diagnosis using Machine Learning Algorithms
... in dataset and generate clear and understandable description of ...a Diabetes Diagnosis system using Machine Learning which has the ability to predict whether the patient has diabetes or ...of ... See full document
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On the impact of using optimization search method in large speaker database based on hybrid modeling over experimental investigation
... difference hybrid pattern classification approach for text independent speaker identification.. system; in these approaches, we combined a hybrid decision tree, GMM and VQ model.[r] ... See full document
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Predicting and Analysis of Student Performance Using Decision Tree Technique
... are using for education data ...Exam model is being constructed which is beneficial for both college and ...this model, institutes can register and host ...This model is an attempt to remove ... See full document
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An Efficient Decision Tree Model for Classification of Attacks with Feature Selection
... on decision tree techniques with special reference to feature ...based decision tree techniques are initially applied on NSL-KDD data set using k-fold validation and 5 different ... See full document
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An Efficient Intrusion Detection using J48 Decision Tree in KDDCUP99 Dataset
... discovery using support vector machine and the gathering using hierarchical bunching ...organization using support vector machine is planned which delivers high true optimistic and correctness as ... See full document
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CLASSIFICATION OF BRAIN TUMORS BY USING DECISION TREE
... The acronym CART stands for Classification And Regression Trees. Both categorical and continuous attributes to build a decision tree can efficiently handle by CART. It handles missing values also. ... See full document
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Cramers V Test Discretization Based Spatial Decision Tree Learning for Land Cover Classification
... spatial decision tree learning models is used to estimate the decision tree classifier that minimizes classification errors as well as salt-and-pepper ...cover classification for ... See full document
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Abstract The Poisson Regression and Negative Binomial
... A decision tree model consists of a set of rules for dividing a large collection of observations into smaller homogeneous group with respect to a particular target ...the decision tree ... See full document
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Analysis Comparison of The Classification Data Mining Method to Predictthe Decisions of Potential Customer Insurance
... Three test parameters that are used as a system evaluation are Precision, Recall and F- measure, with an average result of each test parameter is above 75% [2]. Research [3] discusses the selection of work partners of ... See full document
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