Patient Readmission Prediction
Tranning
Github: prabinpanta0/Patient-Readmission-Prediction
Dataset
{
"model_id": "prabinpanta0/Patient-Readmission-Prediction",
"model_type": "sequence-classification",
"library": {
"random_forest": "scikit-learn",
"logistic_regression": "scikit-learn",
"k_nearest": "scikit-learn",
"svc": "scikit-learn",
"naive_bayes": "scikit-learn",
"neural_network": "keras",
"cross_validation_random_forest": "scikit-learn",
"cross_validation_logistic_regression": "scikit-learn",
"cross_validation_lightgbm": "LightGBM"
},
"model_architectures": {
"random_forest": "RandomForestClassifier",
"logistic_regression": "LogisticRegression",
"k_nearest": "KNeighborsClassifier",
"svc": "SVC",
"naive_bayes": "MultinomialNB",
"neural_network": "NeuralNetwork",
"cross_validation_random_forest": "RandomForestClassifier",
"cross_validation_logistic_regression": "LogisticRegression",
"cross_validation_lightgbm": "LGBMClassifier"
},
"model_paths": {
"random_forest": "model_RandomForestClassifier.pkl",
"logistic_regression": "model_Logistic_Regression.pkl",
"k_nearest": "model_K_nearest.pkl",
"svc": "model_svc.pkl",
"naive_bayes": "model_naive_bayes.pkl",
"neural_network": "neural_network.keras",
"cross_validation_random_forest": "model_rf.pkl",
"cross_validation_logistic_regression": "model_lr.pkl",
"cross_validation_lightgbm": "model_lgbm.pkl"
},
"model_classes": {
"random_forest": "RandomForestClassifier",
"logistic_regression": "LogisticRegression",
"k_nearest": "KNeighborsClassifier",
"svc": "SVC",
"naive_bayes": "MultinomialNB",
"neural_network": "NeuralNetwork",
"cross_validation_random_forest": "RandomForestClassifier",
"cross_validation_logistic_regression": "LogisticRegression"
},
"model_configs": {
"random_forest": {
"n_estimators": 100,
"max_depth": 5
},
"logistic_regression": {
"C": 1,
"max_iter": 1000
},
"k_nearest": {
"n_neighbors": 5
},
"svc": {
"C": 1,
"kernel": "linear"
},
"naive_bayes": {
"alpha": 1
},
"neural_network": {
"input_dim": 10,
"output_dim": 1,
"hidden_dim": 10
},
"cross_validation_random_forest": {
"n_estimators": 100,
"max_depth": 5
},
"cross_validation_logistic_regression": {
"C": 1,
"max_iter": 1000
},
"cross_validation_lightgbm": {
"random_state": 42
}
}
}
metrics
Model |
Accuracy |
Precision |
Recall |
AUC-ROC |
Random Forest |
0.86544 |
0.8734358240972471 |
0.8337883959044369 |
0.8635809449401703 |
Logistic Regression |
0.74736 |
0.7493540051679587 |
0.6928327645051194 |
0.7441573461079813 |
K-Nearest Neighbors |
0.84112 |
0.8543724844493231 |
0.7969283276450512 |
0.838524404786381 |
Support Vector Classifier |
0.84256 |
0.8492462311557789 |
0.8075085324232082 |
0.8405012541634113 |
Naive Bayes |
0.74176 |
0.7692307692307693 |
0.6416382252559727 |
0.7358793535918418 |
Neural Network |
0.87664 |
0.889009009009009 |
0.8419795221843004 |
0.8746042189234755 |
Random Forest (Cross-Validation) |
0.86544 |
0.8734358240972471 |
0.8337883959044369 |
0.8635809449401703 |
Logistic Regression (Cross-Validation) |
0.74736 |
0.7493540051679587 |
0.6928327645051194 |
0.7441573461079813 |
LightGBM (Cross-Validation) |
0.8728 |
0.8773418168964299 |
0.847098976109215 |
0.8712904519100293 |
Random Forest |
Logistic Regression |
K-Nearest Neighbors |
Support Vector Classifier |
Naive Bayes |
Neural Network |
Random Forest (Cross-Validation) |
Logistic Regression (Cross-Validation) |
LightGBM (Cross-Validation) |
1.0 |
0.7453866666666666 |
0.8901866666666667 |
0.8530133333333333 |
0.7455466666666667 |
0.88288 |
1.0 |
0.7453866666666666 |
0.9045866666666667 |
1.0 |
0.7449201741654572 |
0.9005328596802842 |
0.8556024378809189 |
0.7743332882090158 |
0.8964114832535885 |
1.0 |
0.7449201741654572 |
0.910874897792314 |
1.0 |
0.6979827742520399 |
0.8618540344514959 |
0.8272892112420671 |
0.6482320942883046 |
0.849274705349048 |
1.0 |
0.6979827742520399 |
0.8837262012692656 |
1.0 |
0.7427552396345833 |
0.8886139001594574 |
0.8515853672571407 |
0.7401446588709305 |
0.8810145438895148 |
1.0 |
0.7427552396345833 |
0.9034286859660855 |