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decision-tree classifier

by Janet Nichol, Man Sing Wong
"... remote sensing of wildlife habitats using a multi-scale, object-based, ..."
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remote sensing of wildlife habitats using a multi-scale, object-based,

Decision Tree Classifier for Privacy Preservation

by Tejaswini Pawar, Prof Snehal Kamlapur
"... Abstract: In recent year’s privacy preservation in data mining has become an important issue. A new class of data mining method called privacy preserving data mining algorithm has been developed. The aim of these algorithms is to protect the sensitive information in data while extracting knowledge f ..."
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from large amount of data. We focus the general classification in a secured manner and introduce a privacy-preserving decision tree classifier using C4.5 algorithm. The entire original dataset is replaced by unreal dataset for preserving the privacy via dataset complementation. This novel approach can

DECISION TREE CLASSIFIER ON MULTI- PARTIES

by Alka Gangrade, Ravindra Patel
"... Abstract – In this paper, we address Privacy-preserving classification problem in a multi-party sense. We focus the general classification in a secured manner and introduce a Privacy-preserving decision tree classifier using C4.5 algorithm without involving third party. C4.5 algorithm is a software ..."
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Abstract – In this paper, we address Privacy-preserving classification problem in a multi-party sense. We focus the general classification in a secured manner and introduce a Privacy-preserving decision tree classifier using C4.5 algorithm without involving third party. C4.5 algorithm is a software

Building Decision Tree Classifier on Private Data

by Wenliang Du, Zhijun Zhan - IN PROCEEDINGS OF THE IEEE INTERNATIONAL CONFERENCE ON PRIVACY, SECURITY AND DATA MINING , 2002
"... This paper studies how to build a decision tree classifier under the following scenario: a database is vertically partitioned into two pieces, with one piece owned by Alice and the other piece owned by Bob. Alice and Bob want to build a decision tree classifier based on such a database, but due to t ..."
Abstract - Cited by 136 (5 self) - Add to MetaCart
This paper studies how to build a decision tree classifier under the following scenario: a database is vertically partitioned into two pieces, with one piece owned by Alice and the other piece owned by Bob. Alice and Bob want to build a decision tree classifier based on such a database, but due

CLOUDS: A Decision Tree Classifier for Large Datasets

by Khaled Alsabti, Sanjay Ranka, Vineet Singh , 1998
"... Classification for very large datasets has many practical applications in data mining. Techniques such as discretization and dataset sampling can be used to scale up decision tree classifiers to large datasets. Unfortunately, both of these techniques can cause a significant loss in accuracy. We pres ..."
Abstract - Cited by 30 (0 self) - Add to MetaCart
Classification for very large datasets has many practical applications in data mining. Techniques such as discretization and dataset sampling can be used to scale up decision tree classifiers to large datasets. Unfortunately, both of these techniques can cause a significant loss in accuracy. We

THE DECISION TREE CLASSIFIER: DESIGN AND POTENTIAL

by Purdue E-pubs, Hans Hauska, Philip H. Swain, Hans Hauska, Philip H. Swain , 1975
"... 2004 IEEE. This material is provided with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the products or services of the Purdue Research Foundation/University. Internal or personal use of this material is permitted. However, permission to rep ..."
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2004 IEEE. This material is provided with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the products or services of the Purdue Research Foundation/University. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.

A Survey of Decision Tree Classifier Methodology

by S. Rasoul Safavian, David Landgrebe , 1991
"... ..."
Abstract - Cited by 160 (2 self) - Add to MetaCart
Abstract not found

SQL Database Primitives for Decision Tree Classifiers

by Kai-Uwe Sattler, Oliver Dunemann , 2001
"... Scalable data mining in large databases is one of today's challenges to database technologies. Thus, substantial effort is dedicated to a tight coupling of database and data mining systems leading to database primitives supporting data mining tasks. In order to support a wide range of tasks and ..."
Abstract - Cited by 25 (2 self) - Add to MetaCart
and to be of general usage these primitives should be rather building blocks than implementations of specific algorithms. In this paper, we describe primitives for building and applying decision tree classifiers. Based on the analysis of available algorithms and previous work in this area we have identified operations

Methods to Reduce I/O for Decision Tree Classifiers

by Vineet Singh, Anurag Srivastava
"... Classification is an important data mining problem. Although datasets can be quite large in data mining applications, it can be advantageous to use the entire training dataset as opposed to sampling since that can increase accuracy. I/O is a significant component of overall execution time in many de ..."
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decision tree classifiers. We present some new optimizations that work with many of these classifiers on both sequential and parallel processors. For ease of explanation, we describe these optimizations mostly in the context of SPRINT, a classifier developed recently for large problems where the training

A Survey on Privacy Preserving Decision Tree Classifier

by Snehal Kamalapur, Tejaswini Pawar, Prof Snehal Kamalapur
"... In recent year’s privacy preservation in data mining has become an important issue. A new class of data mining method called privacy preserving data mining algorithm has been developed. The aim of these algorithms is protecting the sensitive information in data while extracting knowledge from large ..."
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to incorporating privacy mechanism and allow to hide sensitive pattern or itemset before data mining process is executed. This paper mainly focuses on general classification technique decision tree classifier for preserving privacy. It presents a survey on decision tree learning on various privacy techniques.
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