Patient-Readmission-Prediction

prabinpanta0/Patient-Readmission-Prediction

Patient-Readmission-Prediction is a text classification model from prabinpanta0. Use it when you need a label for a piece of text. It is set up for keras. The card lists the license as mit.

Github: prabinpanta0/Patient-Readmission-Prediction

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Repo size

68.8 MB

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Hugging Face

Repo makeup

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.pkl66.2 MB · 100%

At a glance

Task: Text Classification
Library: keras
License: mit
Access: Public
Created: Sep 5, 2024
Updated: Sep 7, 2024
SHA: 9c89bfe3

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Datasets

prabinpanta0/genki_hospital

Spaces

Wotiperu/Readmisiones

Model card

From the Hugging Face model README

Patient Readmission Prediction

Tranning

Github: prabinpanta0/Patient-Readmission-Prediction

Dataset

Original Source: Kaggle/datasets/dubradave/hospital-readmissions
Import Source: HuggingFace/datasets/prabinpanta0/genki_hospital

{
  "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

Task: Text Classification
Library: keras
License: mit
Languages: en
Created: Sep 5, 2024
Updated: Sep 7, 2024