[PDF] Top 20 Classification with an improved Decision Tree Algorithm
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Classification with an improved Decision Tree Algorithm
... mining, Decision tree structures are a common way to organize classification ...schemes. Classification using a decision tree is performed by routing from the root node until ... See full document
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Web Spam Detection Using Improved Decision Tree Classification Method
... In this paper [2] we have presented a novel algorithm, witch, for the task of detecting Web spam. We have compared witch to several proposed algorithms by using the techniques learning with Graph Regularization, ... See full document
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Managing Asthma in Children And Analyzing Best Possible Treatment With Data Mining Approach of Classification
... rapidly. Decision analysis and knowledge discovery of the high layer is still immature; as a result these lead to the phenomenon of “ information explosion” and “knowledge ...the classification ... See full document
5
Diabetes Diagnosis using Machine Learning Algorithms
... on classification of ...a classification model for diabetes using decision tree, Naïve Bayes, Support vector machine and k nearest neighbour ...The classification model is based on a ... See full document
7
An Improved Algorithm for Inducing Classifica...
... ACO-based algorithm for suggest pronouncement ...class-based decision trees, where each tree is accountable for discerning amongst a specific class worth and all other standards in the class ... See full document
9
Machine Learning Classification Algorithms for Predictive Analysis in Healthcare
... applications. Decision Tree and Support Vector Machine are the machine learning classification algorithm used by the majority of researchers in their heathcare predictive research and are the ... See full document
5
Efficient Processing of Decision Tree Using ID3 & improved C4.5 Algorithm
... Whereas classification predicts categorical (discrete, unordered) labels, prediction models continuous valued ...Many classification and prediction methods have been proposed by researcher in machine ... See full document
6
Student Result Analysis System and Predicting Difficulty Level of Subject
... This system uses java for developing the application. Machine learning techniques are used for prediction of subject difficulty. System uses classification decision tree algorithm (C4.5 ... See full document
5
Pattern Extraction, Classification and Comparison Between Attribute Selection Measures
... ID3 algorithm, C4.5 algorithm and CART ...are decision tree based ...ID3 algorithm is greater than ...C4.5 algorithm. But the accuracy of CART algorithm is greater than ... See full document
5
A Decision-Tree-Based Algorithm for Speech/Music Classification and Segmentation
... The algorithm must be able to operate in real time with a low computational cost and a short ...The algorithm proposed here answers all these require- ments: on one hand, it is highly accurate and robust, ... See full document
14
Analytical Research on Decision Tree Algorithm and Naive Bayesian Classification Algorithm for Data Mining
... The paper presents an extensive modification of ID3 (Iterative Dichotomiser) algorithm and Naïve Bayesian Classification algorithm for data mining. The automated, prospective analyses offered by data ... See full document
12
Steel Buildings Damage Classification by damage spectrum and Decision Tree Algorithm
... programming [17]. Furthermore, damage values were calculated using the decision trees developed in this article. Temban record with the magnitude (M) of 6.2 and distance (R) of 10.8 km from the site were used to ... See full document
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A Novel Decision Tree Based Web Prefetching Scheme
... used decision tree approach to compute the prediction value of hyperlinks, which was used to decide the Web objects to be ...which improved the prediction accuracy and minimized user perceived ... See full document
8
Classification and Analysis of High Dimensional Datasets using Clustering and Decision tree
... conventional decision tree classification, an attribute of a tuple is either unconditional or ...constructing decision tree classifiers on data with uncertain numerical ...on ... See full document
5
II. DECISION TREE CLASSIFICATION
... For the future work, the classification accuracy needs to be improved. This is clear that if the training data set is not uniformly distributed, classic approaches may construct inaccurate trees. We propose ... See full document
5
Improved Accuracy for Decision Tree Algorithm Based on Unsupervised Discretization
... The algorithm constructs a decision tree starting from a training set TS, which is a set of cases, or tuples in the database terminology. Each case specifies values for a collection of attributes and ... See full document
8
Using T3, an improved decision tree classifier, for mining stroke related medical data
... the tree-building phase, at each node, all attributes are examined, in order to select one on which a split will be performed for the ...a tree hierarchy, which determines how important is an at- tribute in ... See full document
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CLASSIFICATION OF DEFECTS IN SOFTWARE USING DECISION TREE ALGORITHM
... of decision rules can be obtained by following the paths from the root of the tree to the ...The algorithm selects attribute that is most useful for classifying examples that means select attribute ... See full document
9
Price Premiums Prediction using Classification and Regression Trees CART Algorithm in eBay Auctions
... intelligent algorithm, the proposed algorithm requires training phase to construct the model of data samples, CART algorithm is a non-parametric procedure which is suitable for dealing with complex ... See full document
6
Performance Analysis of Decision Tree Algorithms on Mushroom Dataset
... Hoeffding Tree: Hoeffding trees were introduced by Domingos and Hutten in high speed data ...Fast Decision Tree leaner .The Hoeffding tree algorithm is the basic theoretical ... See full document
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