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@article{ART002555424},
author={Lee,Seog-Ju},
title={'Faithfulness and Forgiveness' as 'Least Action Principle' through Big Data and Machine Learning in the Analects},
journal={PHILOSOPHY·THOUGHT·CULTURE},
issn={1975-1621},
year={2020},
number={32},
pages={74-98},
doi={10.33639/ptc.2020..32.004}

TY - JOUR
AU - Lee,Seog-Ju
TI - 'Faithfulness and Forgiveness' as 'Least Action Principle' through Big Data and Machine Learning in the Analects
JO - PHILOSOPHY·THOUGHT·CULTURE
PY - 2020
VL - null
IS - 32
PB - Research Institute for East-West Thought
SP - 74
EP - 98
SN - 1975-1621
AB - In this article, we apply the concepts of ‘Faithfulness(忠)’ and ‘Forgiveness(恕)’ to the practical way of practising Ingandaism as presented in the Ongya section of the Analects. We confirm the possibility of applying the results directly to the domain of basic learning in machine learning to obtain its accuracy. As the person as a relational being, while one expresses his or her inner world outwards, one practises various phenomena in his or her life when the complex mind structures respond to external objects. In this process, the causality or correlation of external objects and others from various phenomena is always considered to be the best results selected with the minimal energy. And these best choices and results assess their significance in Newtonian mechanics and Hamilton's principle of least action as the theory of physics. It is significant that the laws of mechanics in physics tested not only the explanatory dimension of the theory of phenomena and objects, but also the possibilities and limitations that can be applied to human practical life based on scientific principles
KW - big data;machine learning;faithfulness and forgiveness;Newtonian mechanics;least action principle
DO - 10.33639/ptc.2020..32.004
ER -

Lee,Seog-Ju. (2020). 'Faithfulness and Forgiveness' as 'Least Action Principle' through Big Data and Machine Learning in the Analects. PHILOSOPHY·THOUGHT·CULTURE, 32, 74-98.

Lee,Seog-Ju. 2020, "'Faithfulness and Forgiveness' as 'Least Action Principle' through Big Data and Machine Learning in the Analects", PHILOSOPHY·THOUGHT·CULTURE, no.32, pp.74-98. Available from: doi:10.33639/ptc.2020..32.004

Lee,Seog-Ju "'Faithfulness and Forgiveness' as 'Least Action Principle' through Big Data and Machine Learning in the Analects" PHILOSOPHY·THOUGHT·CULTURE 32 pp.74-98 (2020) : 74.

Lee,Seog-Ju. 'Faithfulness and Forgiveness' as 'Least Action Principle' through Big Data and Machine Learning in the Analects. 2020; 32 : 74-98. Available from: doi:10.33639/ptc.2020..32.004

Lee,Seog-Ju. "'Faithfulness and Forgiveness' as 'Least Action Principle' through Big Data and Machine Learning in the Analects" PHILOSOPHY·THOUGHT·CULTURE no.32(2020) : 74-98.doi: 10.33639/ptc.2020..32.004

Lee,Seog-Ju. 'Faithfulness and Forgiveness' as 'Least Action Principle' through Big Data and Machine Learning in the Analects. PHILOSOPHY·THOUGHT·CULTURE, 32, 74-98. doi: 10.33639/ptc.2020..32.004

Lee,Seog-Ju. 'Faithfulness and Forgiveness' as 'Least Action Principle' through Big Data and Machine Learning in the Analects. PHILOSOPHY·THOUGHT·CULTURE. 2020; 32 74-98. doi: 10.33639/ptc.2020..32.004

Lee,Seog-Ju. 'Faithfulness and Forgiveness' as 'Least Action Principle' through Big Data and Machine Learning in the Analects. 2020; 32 : 74-98. Available from: doi:10.33639/ptc.2020..32.004

Lee,Seog-Ju. "'Faithfulness and Forgiveness' as 'Least Action Principle' through Big Data and Machine Learning in the Analects" PHILOSOPHY·THOUGHT·CULTURE no.32(2020) : 74-98.doi: 10.33639/ptc.2020..32.004