Input DATASETS private-dataset Language Python License This Notebook has been released under the Apache 2.0 open source license. Continue exploring Input1 file arrow_right_alt Output0 files arrow_right_alt Logs77.5 second run - successful arrow_right_alt Comments2 comments arrow_right_alt...
The present study examines the role of feature selection methods in optimizing machine learning algorithms for predicting heart disease. The Cleveland Heart disease dataset with sixteen feature selection techniques in three categories of filter, wrapper,
Naive Bayes, J48 Decision Tree, and Function Simple Logistic Algorithms were applied to the dataset with the WEKA program. The algorithms were applied to the Kaggle dataset (70,000 records, 11 features, and a target), and the accuracy rates of these data mining classification algorithms were ...
Looking at the significance of the dataset, two datasets i.e. the Cleveland heart disease dataset S1 and Hungarian heart disease dataset (S2) are used, which are available online at the University of California Irvine (UCI) machine learning repository and UCI Kaggle repository, and various ...
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Input DATASETS private-dataset Language Python Table of Contents # Heart Attack Analysis & Prediction using data analysis & data visualization & machine learning & deep learning License This Notebook has been released under the Apache 2.0 open source license. Continue exploring Input1 file arrow_right...
Additionally, transient ischemic attack was self-reported by 41.5% of men and 37.0% of women [39]. The dataset contained details of more than ten cardiovascular-related diseases, and more than 50% of data were not related to CHF or were missing, which made the dataset more challenging for ...