Accurate Prediction of Myocardial Infarction By Comparing Logistic Regression Algorithm with CatBoost Classifier
نویسندگان
چکیده
Aim: The forecast of Myocardial Infarction for humans employing a Machine learning model by corresponding Logistic Regression Algorithm with CatBoost Classifier. accuracy is enhanced utilizing the novel LR Materials and Methods: study utilized total 20 sample iterations, 10 samples per group. Group 1 was analyzed using logistic regression algorithm, while 2 decision tree classifier. statistical power set at 80%, confidence level 95%. Results: outcome 94.61% Classifier 79.516%, both groups are statistically significant as p = 0.015 (<0.05) value in independent T-test between CB Conclusion: This research concludes that algorithm gives most accurate mortality difference 15.1%, compared to
منابع مشابه
Comparing two samples by penalized logistic regression
Inference based on the penalized density ratio model is proposed and studied. The model under consideration is specified by assuming that the log–likelihood function of two unknown densities is of some parametric form. The model has been extended to cover multiple samples problems while its theoretical properties have been investigated using large sample theory. A main application of the densit...
متن کاملA genetic algorithm to select variables in logistic regression: example in the domain of myocardial infarction
Actual use of regression models in clinical practice depends on model simplicity. Reducing the number of variables in a model contributes to this goal. The quality of a particular selection of variables for a logistic regression model can be defined in terms of the number of variables selected and the model's discriminatory performance, as measured by the area under the ROC curve. A genetic alg...
متن کاملPrediction of Antibiotics Residues in Raw Milk by Using Binary Logistic Regression Model
medical compounds, especially antibiotics, in which remains in milk and dairy products on the one hand causes health problems such as allergic reactions and Development of bacterial resistance to antibiotics are a serious threat to the health of consumers , and on the other hand, industrial troubles such as failure to produce fermented products can cause the milk back to the rancher. The purpos...
متن کاملPrediction of Antibiotics Residues in Raw Milk by Using Binary Logistic Regression Model
medical compounds, especially antibiotics, in which remains in milk and dairy products on the one hand causes health problems such as allergic reactions and Development of bacterial resistance to antibiotics are a serious threat to the health of consumers , and on the other hand, industrial troubles such as failure to produce fermented products can cause the milk back to the rancher. The purpos...
متن کاملComparing data mining methods with logistic regression in childhood obesity prediction
The epidemiological question of concern here is " can young children at risk of obesity be identified from their early growth records? " Pilot work using logistic regression to predict overweight and obese children demonstrated relatively limited success. Hence we investigate the incorporation of non-linear interactions to help improve accuracy of prediction; by comparing the result of logistic...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: E3S web of conferences
سال: 2023
ISSN: ['2555-0403', '2267-1242']
DOI: https://doi.org/10.1051/e3sconf/202339904019