Iliou Machine Learning Data Preprocessing Method for Stress Level Prediction - Artificial Intelligence Applications and Innovations (AIAI 2018) Access content directly
Conference Papers Year : 2018

Iliou Machine Learning Data Preprocessing Method for Stress Level Prediction

Theodoros Iliou
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Georgia Konstantopoulou
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Konstantinos Anastasopoulos
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Dimitrios Lymberopoulos
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George Anastassopoulos
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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.
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hal-01821068 , version 1 (22-06-2018)

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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⟩
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