[PDF] Top 20 A comparative study of reduced error pruning method in decision tree algorithms
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A comparative study of reduced error pruning method in decision tree algorithms
... Incremental Pruning to Produce Error Reduction ...Reduce Error Pruning was used where it isolate some data for training and decided when stop from adding more condition to a ...global ... See full document
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A COMPARATIVE STUDY OF DECISION TREE ALGORITHMS FOR CLASS IMBALANCED LEARNING IN CREDIT CARD FRAUD DETECTION
... A wide range of tests is presented to researchers for statistical comparison of classifiers. Among them some are non-parametric while others are parametric. Overall non-parametric tests are considered to be more suitable ... See full document
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Assessment of Decision Tree Algorithms on Student’s Recital
... a decision tree model to predict loyal student to increase educational ...common decision tree algorithms and found CART performed well followed by ...a comparative study ... See full document
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A Survey on Comparative Study of Decision Tree Methods in Data Mining
... mining algorithms, decision makings and other data requirements to eliminate cost and increase ...and decision tree. A decision tree is a graphical depiction of a decision ... See full document
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Improved Decision Tree Induction Algorithm with Feature Selection, Cross Validation, Model Complexity and Reduced Error Pruning
... In this research work, Comparison is made between ID3, C4.5 and C5.0. Among these classifiers C5.0 gives more accurate and efficient output with comparatively high speed. Memory usage to store the ruleset in case of the ... See full document
5
A Comparative Study of Classification Techniques in Data Mining Algorithms
... SVM have attracted a great deal of attention in the last decade and actively applied to various domains applications. SVMs are typically used for learning classification, regression or ranking function. SVM are based on ... See full document
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Simple And Ensemble Decision Tree Classifier Based Detection Of Breast Cancer
... new decision tree classifier Self adaptive NBTree which is a hybrid of Naive Bayes and Decision ...same error rate as it. Venketasan [14] et al studied four decision tree ... See full document
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Study of Pruning Techniques to Predict Efficient Business Decisions for a Shopping Mall
... Cost-Sensitive Decision Trees with Pre-pruning: The algorithms we proposed in this paper are based on [13], incorporating two simple pre-pruning methods, described ...2-Level Tree. With ... See full document
5
Selective Rademacher Penalization and Reduced Error Pruning of Decision Trees
... feasibility study of the new technique of Rademacher penalization, rather than to aim at generalization error bounds directly applicable in the real ...test error, it is never totally ...this ... See full document
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Using Reduced Set of Features to Detect Spam in Twitter Data with Decision Tree and KNN Classifier Algorithms
... and study the user’s behaviour, characteristics in the social media, etc ...learning algorithms such as supervised and unsupervised algorithms and statistical ... See full document
7
Performance Analysis of Classification Tree Learning Algorithms
... a tree based structure which is a concept of data mining (machine learning) ...a method where one can classify future data into known ...include decision trees, Naïve Bayes, Logistic regression, ... See full document
6
Prediction of Optimum Treatment in Beta-Thalassemia Patients with Hepatitis C Virus Infection
... a study, Wongseree ...a decision tree, which is evolved by genetic ...C4.5 decision-tree algorithm and Reduced Error Pruning (REP) tree as one of the Fast ... See full document
12
Health Prediction System by using Data Mining
... mining algorithms for predicting survival of CHD patients based on 1000 cases ...mining algorithms to develop the prediction models using the 502 ...the decision trees models came out to be the worst ... See full document
5
Combination of Text Mining and Corrective Neural Network in Short-term Load Forecasting
... ANN method outperformed the ARMA ...Machines(SVM) method, proposed by Vapik[12], implements the structural risk minimization (SRM) principle rather than empirical risk minimization principle implemented by ... See full document
7
EDUCATIONAL MODELLING IN CLOUD COMPUTING USING IMS LEARNING DESIGN
... the method Classification And Regression Tree (CART) successfully implemented the answers given by the user and the data provided by the ...CART method produces shorter rules, but has a high accuracy ... See full document
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AN OPTIMISED INTELLECTUAL AGENT BASED SECURE DECISION SYSTEM FOR HEALTH CARE
... each data point to its nearest center. A popular heuristic for k-means clustering is Lloyd's algorithm. In this paper, we present a simple and efficient implementation of Lloyd's k-means clustering algorithm, which we ... See full document
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Quantifying pruning impacts on olive tree architecture and annual canopy growth by using UAV-based 3D modelling
... with height information, which was created from the 3D point cloud, and (3) the ortho-mosaicked image, with RGB information on every pixel. In this research, Agisoft PhotoScan Professional software, version 1.2.4 build ... See full document
15
Study of Decision Tree Classification Algorithms using Matrimonial System
... of decision tree ...scalable decision tree ...the decision tree, rather it partitions the training data set recursively using breadth- first greedy technique until each partition ... See full document
6
Internet of things based Early Detection of Diabetes using Machine Learning Algorithms: Dpa
... new decision tree algorithm names Diabetics Prediction Algorithm (DPA) based on the Machine learning, uses dataset collected using IOT Diabetes ...published algorithms [4-7] ... See full document
5
Efficient Algorithms for Decision Tree Cross-validation
... The algorithm from Figure 6 can be adapted for parallel cross-validation as shown in Figure 7. The first step is again sorting the examples. Note that the time for finding a split is dominated by the sorting time as the ... See full document
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