Home Talk Free Talk 고딩 스펙을 왜 IEEE에 올려서 검색퀄 떨어지게 하고 난리냐 This topic has [4] replies, 0 voices, and was last updated 3 years ago by ㄹ. Now Editing “고딩 스펙을 왜 IEEE에 올려서 검색퀄 떨어지게 하고 난리냐” Name * Password * Email Topic Title (Maximum Length 80) https://ieeexplore.ieee.org/document/9742757 Conferences >2022 Second International Con... A Performance Analysis of Depression Ratio using Machine Learning Approaches Maria Sultana Keya; Alex Han Publisher: IEEE Abstract: Depression is much more than just tiredness or unpleasantness for a few days. Some individuals believe that depression is a minor ailment rather than a serious medical disease. However, depression is not a weakness that can be “snapped out of” by “getting yourself together.” Depression is a disease which can be recovered by taking proper treatment and support. Depression symptom may be easily detected when a man or woman goes into depression. For the purpose of medication and assistance purpose, prediction of prognosis of the depression is important. In this research paper, five Machine Learning algorithms such as Decision Tree Classifier (DTC), Random Forest Classifier (RFC), Multi-layer Perceptron Classifier (MLP), Support Vector Machine (SVM), and AdaBoost Classifier are used to apply to for prediction of depression prognosis. As a result, it is found that SVM machine learning algorithm performs the best. It has an accuracy rate of 85 percent. Also indicated is the age at which men and women are most likely to become depressed. Support Vector Machine classifiers also have low FP (False Positive) and FN (False Negative) rates. Some visualization is applied to generate a view of depression rate in different types of people. This study also used principal component analysis to Figure out the selective data for analysis algorithms. ieeexplore 머신러닝 논문검색하면 이런 엄마찬스 아빠찬스 사돈팔촌찬스 다쓰는 고삐리들땜에 막상 논문 찾는 사람들에게 개허접 지뢰가 많아져버렸다. IEEE에 가짜논문 대리논문쓰면 대학잘가? 그리고 저자리스트 맨뒤에 있어서 누가보면 고삐리가 논문 지도교수나 연구스폰서인줄 알겠어. I agree to the terms of service Update List
