Classification on Kaggle Cardiovascular Disease Dataset I benchmark leaderboard · SOTA2 Research

Classification on Kaggle Cardiovascular Disease Dataset I

82.3AccuracyCNN–LSTM + KNN + XGB

Evaluation Results

Method	Links
CNN–LSTM + KNN + XGB2026.01		82.3	84	83.5	83.6
CNN–LSTM2026.01		80	81.8	81.4	81.3
RF + DT + NB + LR2026.01		79.5	79.7	79.4	79.5
RF + DT + KNN + NB + SVM + LGBM + XGB + MLP + LR2026.01		79	79.2	79	79.1
XGB2026.01		78.9	79.3	79.2	79.4
CNN2026.01		78.8	80	79.8	80.1
KNN2026.01		78.3	79.1	79.2	79.4
LGBM2026.01		78.1	78.9	78.6	78.7
LSTM2026.01		78	80.1	79.9	80
AdaBoost2026.01		77.9	78.8	78.7	78.9
RF2026.01		77.8	78.1	78.2	78.3
SVM2026.01		77.5	77.9	77.7	77.8
DT2026.01		77.3	78.2	78.3	78.4
LR2026.01		76.8	77.8	77.4	77.2
MLP2026.01		76.8	77.9	77.8	77.6
NB2026.01		75.5	75.9	76	75.8