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An Efficient First Order Logical Casual Decision Tree in High Dimensional Dataset

S.Preethi 1 , C.Rathika 2

  1. Dept. of Computer Science, Sri Ramakrishna college of Arts and Science for women, Coimbatore, India.
  2. Dept. of Computer Science, Sri Ramakrishna college of Arts and Science for women, Coimbatore, India.

Correspondence should be addressed to: preethisenthil1969@gmail.com .

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-2 , Page no. 73-78, Feb-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i2.7378

Online published on Feb 28, 2018

Copyright © S.Preethi , C.Rathika . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: S.Preethi , C.Rathika, “An Efficient First Order Logical Casual Decision Tree in High Dimensional Dataset,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.2, pp.73-78, 2018.

MLA Style Citation: S.Preethi , C.Rathika "An Efficient First Order Logical Casual Decision Tree in High Dimensional Dataset." International Journal of Computer Sciences and Engineering 6.2 (2018): 73-78.

APA Style Citation: S.Preethi , C.Rathika, (2018). An Efficient First Order Logical Casual Decision Tree in High Dimensional Dataset. International Journal of Computer Sciences and Engineering, 6(2), 73-78.

BibTex Style Citation:
@article{_2018,
author = {S.Preethi , C.Rathika},
title = {An Efficient First Order Logical Casual Decision Tree in High Dimensional Dataset},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {2 2018},
volume = {6},
Issue = {2},
month = {2},
year = {2018},
issn = {2347-2693},
pages = {73-78},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1703},
doi = {https://doi.org/10.26438/ijcse/v6i2.7378}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i2.7378}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1703
TI - An Efficient First Order Logical Casual Decision Tree in High Dimensional Dataset
T2 - International Journal of Computer Sciences and Engineering
AU - S.Preethi , C.Rathika
PY - 2018
DA - 2018/02/28
PB - IJCSE, Indore, INDIA
SP - 73-78
IS - 2
VL - 6
SN - 2347-2693
ER -

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Abstract

Uncovering causal interactions in data is a most important objective of data analytics. Causal relationships are usually exposed with intended research, e.g. randomised controlled examinations, which however are costly or insufficient to be performed in several cases. In this research paper aims to present a new Casual Decision tree structure of first-order logical casual decision tree called FOL-CDT structure. The proposed method follows a well-recognized pruning approach in causal deduction framework and makes use of a standard arithmetical test to create the causal relationship connecting a analyst variable and the result variable. At the similar instance, by taking the advantages of standard decision trees, a FOL-CDT presents a compact graphical illustration of the causal relationships with pruning method, and building of a FOL-CDT is quick as a effect of the divide and conquer strategy in use, making FOL-CDTs realistic for representing and resulting causal signals in large data sets.

Key-Words / Index Term

Data Mining, First order Logical, Decision Tree, Pruning, Classification

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