Some pretrained models of project PHBS_MLF_2019_Project .

Navigation

Report	Code	Data & Model
📄 Report in PDF	Correlation and engineering	Description
-	Cleaning	Train.csv
-	Baselines and trees	Test.csv
-	ANN	Models(You are here)

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Models available

• Logistic Regession

  • LogisticRegression_04161442.model

• Random Forest (only parameters uploaded due to file size)

  • RandomForest_04160226_88.74%.txt

• GBDT / DART in LightGBM

  • LightGBM_04160053.model
  • LightGBM_04161347.model

• GBDT in XGBoost

  • XGBoost_04152029.model

• ANN (only parameters uploaded due to file size)

  • final_ann_model_mod.pt

Filename explained

Type	Filename
Model dumped	{model} _ {datetime} . model
	e. g. LogisticRegression_04161442. model
Confusion matrix	{model} _ {datetime}. png
	e. g. LogisticRegression_04161442. png
Parameter	{model} _ {datetime} _ {accuracy} %. txt
	e. g. LogisticRegression_04161442_89. 04%. txt

For ANN parameters: final_ann_model_mod.pt .

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This project is under MIT license.