A Novel Machine Learning Data Preprocessing Method for Enhancing Classification Algorithms Performance

Iliou, Theodoros; Anagnostopoulos, Christos‐Nikolaos; Nerantzaki, Marina; Anastassopoulos, George

doi:10.1145/2797143.2797155

Cited by 22 publications

(10 citation statements)

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“…In this paper, we used Principal Component Analysis (PCA) and a novel machine learning data preprocessing method that we have proposed in [7] in order to compare our suggested method performance with PCA.…”

Section: Data Pre-processing Methodsmentioning

confidence: 99%

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Machine Learning Preprocessing Method for Suicide Prediction

Iliou

Κωνσταντοπούλου

Ntekouli

et al. 2016

IFIP Advances in Information and Communication Technology

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The main objective of this study was to find a preprocessing method to enhance the effectiveness of the machine learning methods in datasets of mental patients. Specifically, the machine learning methods must have almost excellent classification results in patients with depression who have thoughts of suicide, in order to achieve the sooner the possible the appropriate treatment. In this paper, we establish a novel data preprocessing method for improving the prognosis' possibilities of a patient suffering from depression to be leaded to the suicide. For this reason, the effectiveness of many machine learning classification algorithms is measured, with and without the use of our suggested preprocessing method. The experimental results reveal that our novel proposed data preprocessing method markedly improved the overall performance on initial dataset comparing with PCA and Evolutionary search feature selection methods. So this preprocessing method can be used for significantly boost classification algorithms performance in similar datasets and can be used for suicide tendency prediction.

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Section: Data Pre-processing Methodsmentioning

confidence: 99%

“…The rows (variables) RS_Mean_classm_rowj, RS_Median_classm_rowj, Fi-nal_Meanm_rowj and Final_Medianm_rowj for every class are selected from previous step and then are placed in a new table [7].…”

Section: Stepmentioning

confidence: 99%

Machine Learning Preprocessing Method for Suicide Prediction

Iliou

Κωνσταντοπούλου

Ntekouli

et al. 2016

IFIP Advances in Information and Communication Technology

Self Cite

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“…During the data preprocessing process, heterogeneous properties in the dataset will disappear, because heterogeneous datasets will affect the results in generalization [81]. Because the dataset preprocessing will be able to restore missing data and normalize the dataset [20][82]; and can change the format of datasets to be easier and more effective when they are processed [83].…”

Section: The Isbsg Datasetmentioning

confidence: 99%

Optimizing Software Effort Estimation Models Based On Metaheuristic Methods: A Proposed Framework

Marco¹

2019

IJATCSE

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Software effort estimation are part of the field of project management in software that is very important for development efforts. Software development planning is something very complex and serious, which determines the success of a software project. Because of the lack of good requirements and information, it causes software project failures. Although there are many studies that aim to solve the problem of noisy, irrelevant and excessive data to achieve accuracy. The purpose of this study is to combine metaheuristic optimization techniques as a framework for using Machine Learning models. By proposing a hybrid estimation model based on a combination of the Satin Bowerbird Optimizer (SBO) algorithm and Support Vector Regression (SVR) to improve the accuracy of software estimation efforts. This study is to determine the effort estimation and duration estimation. The proposed framework is based on theoretical concepts. the proposed model will be tested using a heterogeneous dataset, namely the ISBSG dataset. the results of the study are expected to be used as decision making as the initial planning of software project development.

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“…Iliou method uses Statistics and Linear Algebra methods like the dot (inner) product of dataset vectors in conjunction with some descriptive statistics [24].…”

Section: Data Preprocessingmentioning

confidence: 99%

Iliou Machine Learning Data Preprocessing Method for Stress Level Prediction

Iliou

Κωνσταντοπούλου

Stephanakis

et al. 2018

IFIP Advances in Information and Communication Technology

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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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A Novel Machine Learning Data Preprocessing Method for Enhancing Classification Algorithms Performance

Cited by 22 publications

References 1 publication

Machine Learning Preprocessing Method for Suicide Prediction

Machine Learning Preprocessing Method for Suicide Prediction

Optimizing Software Effort Estimation Models Based On Metaheuristic Methods: A Proposed Framework

Iliou Machine Learning Data Preprocessing Method for Stress Level Prediction

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