Vishal Rana, Jianhao Peng, Chao Pan, Hanbaek Lyu, Albert Cheng, Minji Kim, Olgica Milenkovic
Interpretable online network dictionary learning for inferring long-range chromatin interactions
PLoS computational biology
paper presents comprehensive exploration machine learning algorithms mlas feature selection techniques accurate heart disease prediction hdp modern healthcare focusing diverse datasets encompassing various challenges research sheds light optimal strategies early detection mlas decision trees dt random forests rf support vector machines svm gaussian naive bayes nb others studied precision recall metrics emphasized robust predictions study addresses challenges realworld data data cleaning onehot encoding enhancing integrity predictive models feature extraction techniquesrecursive feature extraction rfe principal component analysis pca univariate feature selectionplay crucial role identifying relevant features reducing data dimensionality findings showcase impact techniques improving prediction accuracy optimized models dataset achieved grid search hyperparameter tuning configurations meticulously outlined notably remarkable 9912 accuracy achieved first kaggle dataset showcasing potential accurate hdp model robustness across diverse datasets highlighted caution overfitting study emphasizes need validation unseen data encourages ongoing research generalizability serving practical guide research aids researchers practitioners hdp model development influencing clinical decisions healthcare resource allocation providing insights effective algorithms techniques paper contributes reducing heart diseaserelated morbidity mortality supporting healthcare communitys ongoing efforts