NDLI: Noise Reduction Approach for Decision Tree Construction: A Case Study of Knowledge Discovery on Climate and Air Pollution

Content Provider	IEEE Xplore Digital Library
Author	Fukuda, K.
Copyright Year	2007
Description	Author affiliation: Dept. of Math. & Stat., Comput. Sci. & Software Eng., Canterbury Univ., Christchurch (Fukuda, K.)
Abstract	Data mining is more effective on noisy time series with appropriate data pre-processing. Singular spectrum analysis (SSA) is explored as the noise reduction approach for a decision tree classifier for noisy data. SSA provides groups of additive components, from low to high frequency, by decomposing the noisy time series. In this study, the noisy climate data is decomposed by SSA and is used to construct decision trees to predict the carbon monoxide (CO) air pollution levels. Analysis shows that separating out seasons from the annual data helps the algorithm; the classification accuracy improvements vary by season, with the maximum improvement (from 60.7% to 77.3%) found in summer by removing 6.42% of the high frequency signals, while autumn showed no improvement. Examining decision tree structures provides threshold climate values that impact on different CO levels, e.g., a light wind speed of les 2.5 m/s and any level of temperature inversion formation is found to associate with the high CO level (> 0.70 $mg/m^{3}).$ Overall, data pre-processing using SSA is encouraging to improve the results of any time series data mining approach. Examining decision trees of the climate and air pollution helps increase knowledge about the data, and the studied approaches can be adaptable for various future environmental studies
Starting Page	697
Ending Page	704
File Size	9736359
Page Count	8
File Format	PDF
ISBN	1424407052
DOI	10.1109/CIDM.2007.368944
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-03-01
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Additive noise Noise reduction Carbon dioxide climate Data mining Noise level Singular Spectrum Analysis decision trees Air pollution Frequency Decision trees Signal analysis Classification tree analysis
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in