Heart Disease Prediction Using K-Nearest Neighbor

Rahmat, Dadi; Putra, Andika A.; Hamrin,; Setiawan, Andri

doi:10.1109/iceei52609.2021.9611110

Cited by 13 publications

(7 citation statements)

References 8 publications

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“…However, it should be noted that the test error for the KNN model is higher than that of all other regression models under consideration. Dragomir (2010) noted different results than this study, where they noted that KNN is a good model for predicting air quality [13]. The reason for the discrepancy between our results and the other study [13] may be due to differences in the specific dataset used, the selection of input features, or adjustments in the experimental setup, all of which may have affected the KNN model performance assessment and suitability for the air quality data used in this study.…”

Section: Comparing Different Regression Modelscontrasting

confidence: 79%

“…Furthermore, machine learning-based regression models, including support vector regression, random forests, and neural networks, have gained popularity due to their ability to handle high-dimensional data and capture intricate relationships [12]. These models can handle nonlinearities, interactions, and complex dependencies, enhancing the accuracy of air quality predictions [13]. Overall, the variety of regression models available provides researchers with powerful tools to analyze and predict air quality, contributing to advancing our understanding and management of air pollution.…”

Section: So2 (Ppb)mentioning

confidence: 99%

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Unveiling the Predictive Capabilities of Machine Learning in Air Quality Data Analysis: A Comparative Evaluation of Different Regression Models

Khanaum,

Borhan,

Ferdoush

et al. 2023

OJAP

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Air quality is a critical concern for public health and environmental regulation. The Air Quality Index (AQI), a widely adopted index by the US Environmental Protection Agency (EPA), serves as a crucial metric for reporting site-specific air pollution levels. Accurately predicting air quality, as measured by the AQI, is essential for effective air pollution management. In this study, we aim to identify the most reliable regression model among linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), logistic regression, and K-nearest neighbors (KNN). We conducted four different regression analyses using a machine learning approach to determine the model with the best performance. By employing the confusion matrix and error percentages, we selected the best-performing model, which yielded prediction error rates of 22%, 23%, 20%, and 27%, respectively, for LDA, QDA, logistic regression, and KNN models. The logistic regression model outperformed the other three statistical models in predicting AQI. Understanding these models' performance can help address an existing gap in air quality research and contribute to the integration of regression techniques in AQI studies, ultimately benefiting stakeholders like environmental regulators, healthcare professionals, urban planners, and researchers.

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Section: Comparing Different Regression Modelscontrasting

confidence: 79%

Section: So2 (Ppb)mentioning

confidence: 99%

Unveiling the Predictive Capabilities of Machine Learning in Air Quality Data Analysis: A Comparative Evaluation of Different Regression Models

Khanaum,

Borhan,

Ferdoush

et al. 2023

OJAP

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“…Some have just graduated from elementary-school, some have just graduated from college. However, high school is still the majority of these students (Rahman Ahdori & Setiawan, 2021). At that time, the Al-Fatah Islamic boarding school had become a trending topic like the New York Times, Time, and BuzzFeed.…”

Section: Discussion Results the History Of The Al-fatah Islamic Board...mentioning

confidence: 99%

Social Solidarity and Waria Religiousity: A Netnographic Study of Al-Fatah Islamic Boardingschool Yogyakarta

Leany

Sari

2022

j.ilm.mhs.raushanfikr

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Research on transgender religiosity is interesting to study more deeply. This is because of the public’s view that transgenders are justified as a nuisance or disturbing people’s lives. However, something different happened at the Al-Fatah Islamic Boarding School. Pesantren is used as a place to instill religious values in transgender people. So that it becomes a place for waria to develop religion, or as a place for waria to return to the right path, without the element of coercion. Never view transgenders negatively. The purpose of this study is to get an idea of how the public views transgenders in Al-Fatah Islamic Boarding School and a picture of the growth of transgender religious values in Al-Fatah Islamic Boarding School. This research method uses a descriptive qualitative approach with a virtual netnography approach. Netnography is the process of browsing an entity while using internet processes. This article proves the tips on community solidarity in instilling religious values in transgender women at Al-Fatah Islamic Boarding School there are also other findings, namely the side of tolerance for human characters that are different from other

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“…Similarly, D. Rahmat [4] used a SelectKbest feature selection technique in association with 10-Fold cross validation technique. They used KNN imputation which helps in filling the blank values (Nan) if any present in the dataset.…”

Section: Related Workmentioning

confidence: 99%

“…An important assumption is that the stream of data is constant over time. They have also used a 10-cross validation technique used in [4]. The accuracy results from both the types of trees are the same but Hoeffding takes a smaller number of nodes for classification compared to J48 resulting in a faster computation process.…”

Section: Related Workmentioning

confidence: 99%

Early-Stage Disease Prediction from Various Symptoms Using Machine Learning Models

Ajmera,

Pandey,

Singh

et al. 2024

EAI Endorsed Trans IoT

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Development and exploration of several Data analytics techniques in various real-time applications (e.g., Industry, Healthcare Neuroscience) in various domains have led to exploitation of it to extract paramount features from datasets. Following the introduction of new computer technology, the health sector had a significant transformation that compelled it to produce more medical data, which gave rise to a number of new disciplines of study. Quite a few initiatives are made to deal with the medical data and how its usage can be helpful to humans. This inspired academics and other institutions to use techniques like data analytics, its types, machine learning and different algorithms, to extract practical information and aid in decision-making. The healthcare data can be used to develop a health prediction system that can improve a person's health. Based on the dataset provided, making accurate predictions in early disease prediction benefits the human community.

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Heart Disease Prediction Using K-Nearest Neighbor

Cited by 13 publications

References 8 publications

Unveiling the Predictive Capabilities of Machine Learning in Air Quality Data Analysis: A Comparative Evaluation of Different Regression Models

Unveiling the Predictive Capabilities of Machine Learning in Air Quality Data Analysis: A Comparative Evaluation of Different Regression Models

Social Solidarity and Waria Religiousity: A Netnographic Study of Al-Fatah Islamic Boardingschool Yogyakarta

Early-Stage Disease Prediction from Various Symptoms Using Machine Learning Models

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