Skip to Main content Skip to Navigation
Conference papers

Iliou Machine Learning Data Preprocessing Method for Stress Level Prediction

Abstract : Data pre-processing is an important step in the data mining process. Data preparation and filtering steps can take considerable amount of processing time. Data pre-processing includes cleaning, normalization, transformation, feature extraction and selection. In this paper, Iliou and PCA data preprocessing methods evaluated in a data set of 103 students, aged 18–25, who were experiencing anxiety problems. The performance of Iliou and PCA data preprocessing methods was evaluated using the 10-fold cross validation method assessing seven classification algorithms, IB1, J48, Random Forest, MLP, SMO, JRip and FURIA, respectively. The classification results indicate that Iliou data preprocessing algorithm consistently and substantially outperforms PCA data preprocessing method, achieving 98.6% against 92.2% classification performance, respectively.
Document type :
Conference papers
Complete list of metadatas

Cited literature [34 references]  Display  Hide  Download

https://hal.inria.fr/hal-01821068
Contributor : Hal Ifip <>
Submitted on : Friday, June 22, 2018 - 11:45:50 AM
Last modification on : Friday, August 9, 2019 - 4:14:27 PM
Long-term archiving on: : Tuesday, September 25, 2018 - 2:33:04 PM

File

467708_1_En_30_Chapter.pdf
Files produced by the author(s)

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Citation

Theodoros Iliou, Georgia Konstantopoulou, Ioannis Stephanakis, Konstantinos Anastasopoulos, Dimitrios Lymberopoulos, et al.. Iliou Machine Learning Data Preprocessing Method for Stress Level Prediction. 14th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), May 2018, Rhodes, Greece. pp.351-361, ⟨10.1007/978-3-319-92007-8_30⟩. ⟨hal-01821068⟩

Share

Metrics

Record views

188