decision-tree induction
Clus-DTI: improving decision-tree classification with a clustering-based decision-tree induction algorithm
... Abstract Decision-tree induction is a well-known tech- nique for assigning objects to categories in a white-box fash- ...Most decision-tree induction algorithms rely on a sub- ...
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Feature Selection Using Decision Tree Induction in Class level Metrics Dataset for Software Defect Predictions
... on Decision Tree ...on decision tree classifiers used in the classification ...named Decision Tree Induction Rule based (DTIRB) feature ...by decision tree ...
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Automatic Partial Parsing Rule Acquisition Using Decision Tree Induction
... a tree-annotated corpus using a decision tree ...using decision tree induction, with features of contextual and lexical information for the classification; and (3) verifying ...
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Cost-Sensitive Classification: Empirical Evaluation of a Hybrid Genetic Decision Tree Induction Algorithm
... a decision tree induction algo- ...the decision tree, including both the costs of tests (features, measurements) and the costs of classification ...
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VPRSM based Improved Decision Tree Induction Approach for HandlingUncertain Data
... intelligent decision tree ...in Decision Tree(DT) classification handles uncertainties in the training data and results in generation of more precise decision ...DT induction ...
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Cybercrime Profiling: Decision Tree Induction, Examining Perceptions of Internet Risk and Cybercrime Victimisation
... tree structure where each internal node denotes a test on an attribute, each branch represents an outcome of the test, and leaf nodes represent classes or class distribution” [3]. It is therefore possible for the ...
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Title: USING DECISION TREE INDUCTION TO PREDICT THE TYPE OF EATING DISORDER
... A classification problem consists of properly segregating records into specific classes based on the attribute values. To build a classification model, the labeled data set is initially partitioned into two disjoint ...
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A survey of cost sensitive decision tree induction algorithms
... top-down tree induction algorithms can be adapted so that the total test cost for any example will be no more than a pre-specified ...the tree induction process by only considering those ...
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Generating Optimized Decision Tree Based on Discrete Wavelet Transform Kiran Kumar Reddi* 1Ali Mirza Mahmood2 K.Mrithyumjaya Rao 3
... In decision tree induction the entire data in the training set is used as root node for the ...of decision trees can be generated depending upon two main parameters, one is heuristic function ...
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Classification Using Max-Margin and Kernel Dimensionality Reduction
... of decision tree classifiers does not require any domain knowledge or parameter setting, and therefore is appropriate for exploratory knowledge ...the tree size is independent of the database size ...
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A Survey Paper on Phishing Attacks with New Unsupervised Learning Model
... Decision tree induction is the learning of decision trees from class labeled training ...A decision tree is a flow chart like tree structure, where each internal node ...
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An Efficient Mining Algorithm for Determining Related Item Sets using Classification and Association Rules
... In the present days, data mining is the advanced research area because it is one of the important step in the knowledge discovery process. This paper presents an experimental study of finding the frequent item sets by ...
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Study of Various Decision Tree Pruning Methods with their Empirical Comparison in WEKA
... Decision tree Induction is top down approach which starts from the root node and explore from top to ...the decision tree. Basic algorithm for constructing decision tree ...
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A Survey based Research for Data Mining Techniques to Forecast Water Demand in Irrigation
... The paper has narrated the actual scenario in agriculture for the sake of water demand and supply chain mechanism. It has been concluded that data mining can play an effective role to address this problem. As a result of ...
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Sentiment Analysis of Movie Reviews using Machine Learning Techniques
... The research started with analyzing different research and review papers on sentiment analysis and the summary for each paper was created by reading and understanding the paper. Study of frequently used classification ...
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Title: DATA MINING TO ELICIT PREDOMINANT FACTORS CAUSING INFERTILITY IN WOMEN
... different decision tree induction methods and a comparative study of the methods is also ...through decision tree induction and this is used to build a software model for the ...
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Data Mining Techniques in Parallel Environment A Comprehensive Survey
... Data mining is the process of discovering interesting and useful patterns and relationships in large volumes of data. The valuable knowledge can be discovered through the process of data mining for the further use and ...
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Protein Function Prediction Model Using Multilabel Classification Algorithm
... for decision tree induction to introduced for Hierarchical multi-label classification with a various set of bio information's which involves predicting the level protein function and also contains a ...
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An Optimal Clustering Approach In Web Usage Mining For Recommendation System
... Web usage data, association rules, item logical classification, and decision tree induction are used for better recommendations on this structure.. in this analysis tries[r] ...
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Survey Paper for Credit Card Fraud Detection Using Data Mining Techniques
... “Decision Tree Induction Algorithm” which is used for Credit Card Fraud ...method, decision tree approach is a new cost sensitive technique compared with well-known traditional ...
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