KotaShimomura / COVID-19-Hospital-Stay-Prediction

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COVID-19-Hospital-Stay-Prediction

ゼミコンペのbaseline,多クラス分類用code

実行環境

ubuntu : 20.04
Docker version 20.10.8

Data Description

train.csv - training set that contains Stay_Days that is classified into 11 categories.
test.csv - test set that does not contain Stay_Days.
simple_submission.csv - a sample submission file in the correct format.

Data Fields

case_id
Hospital
Hospital_type
Hospital_city
Hospital_region
Available_Extra_Rooms_in_Hospital - Number of extra rooms available in the hospital
Department - Department overlooking the case: radiotherapy, anesthesia, gynecology, TB & Chest disease or surgery
Ward_Type - R, S, Q, P, T or U
Ward_Facility - F, E, D, B, A or C
Bed_Grade - Condition of bed in the ward
patientid
City_Code_Patient - City Code for the patient
Type of Admission - Admission type registered by the hospital: Emergency, Trauma or Urgent
Illness_Severity - Severity of the illness recorded at the time of admission: Extreme, Moderate or Minor
Patient_Visitors -
Age - 0-10, 11-20, 21-30, 31-40, 41-50, 51-60, 61-70, 71-80, 81-90 or 91-100
Admission_Deposit - Deposit at the admission time
Stay_Days - Stay days by the patient: 0-10, 11-20, 21-30, 31-40, 41-50, 51-60, 61-70, 71-80, 81-90, 91-100, 101-

実行用ファイル

lgbm_baseline.ipynb

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