Publications by R on notast
Predicting pneumonia outcomes: Modelling via DataRobot API
This post is a supplementary material for an assignment. The assignment is part of the Augmented Machine Learning unit for a Specialised Diploma in Data Science for Business. The aim of this project is to classify if patients with Community Acquired Pneumonia (CAP) became better after seeing a doctor or became worse despite seeing a doctor. Previ...
6984 sym R (6149 sym/14 pcs) 6 img
Predicting pneumonia outcomes: Results (using DataRobot API)
This post is a supplementary material for an assignment. The assignment is part of the Augmented Machine Learning unit for a Specialised Diploma in Data Science for Business. The aim of this project is to classify if patients with Community Acquired Pneumonia (CAP) became better after seeing a doctor or became worse despite seeing a doctor. Previ...
8333 sym R (11269 sym/17 pcs) 22 img
Hierarchical forecasting of hospital admissions
Introduction Visualization 1. Trend 2. Seasonality Trend and seasonality 3. Anomaly Conclusion Introduction The aim of this series of blogs is to do time series forecasting with libraries that conform to tidyverse principles and there are two of these time series meta-packages modeltime which is created to be the time series equivalent of tid...
6646 sym R (5229 sym/18 pcs) 28 img
Hierarchical forecasting of hospital admissions- EDA part 2
Introduction The aim of this series of blog is to predict monthly admissions to Singapore public acute adult hospitals. The dataset starts from Jan 2016 and ends in Feb 2021. library(tidyverse) library(timetk) library(fpp3) # cleaned up dataset downloaded from my github. Clean up of OG dataset done in 1st post raw<- read_csv("https://raw.github...
7583 sym R (15281 sym/27 pcs) 28 img
Hierarchical forecasting of hospital admissions- Classical forecast
Intro Reconciliation Dataset Feature Engineering Models Evaluation ARIMA ARIMA vs ETS Performance for each level Cluster level National level Conclusion Error Intro The aim of this series of blog is do predict monthly admissions to Singapore public acute adult hospitals. The dataset starts from Jan 2016 and ends in Feb 2021. EDA for the data...
6653 sym R (9205 sym/11 pcs) 6 img
Hierarchical forecasting of hospital admissions- ML approach (screen variables)
1 Intro 2 Data wrangling 2.1 Long format with aggregated values 2.2 Extend into the future 2.3 External regressor 2.3.1 Lags and rolling lags 2.3.2 Covid 2.3.3 Time series features 3 Splitting 4 Pre-processing recipes Pre-processing order 5. Modelling Workflow 6. Evaluate 6.1 Evaluate against the training set What’s inside the calibrat...
9496 sym R (18078 sym/24 pcs) 4 img
Hierarchical forecasting of hospital admissions- ML approach (modeltime package)
1 Intro 2 Cross validation Metrics 3. Pre-processing 3.1 Base recipe 3.2 Spline recipe 3.3 Prophet boost recipe 4 Modelling 4.1 GLM 4.2 MARS 4.3 RF 4.4 XGB 4.5 Prophet boost 5. Evaluation Conclusion 1 Intro The aim of this series of blog is to predict monthly admissions to Singapore public acute adult hospitals. EDA for the dataset was exp...
5377 sym R (12499 sym/21 pcs) 4 img
Hierarchical forecasting of hospital admissions- ML approach (ensemble)
1. Recap 2 Tune again Modelling Retuning 2.1 Retune Random Forest 2.2 Retune Prophet boost 2.3 Performance (after retuning) 3 Ensemble 3.1 Peformance (ensemble) 4 Performance (individual levels) Hospital Cluster level National level 5 The future Hospital Cluster National 6 KIV Plans Errors 1. Recap The aim of this series of blog is to p...
5464 sym R (12776 sym/23 pcs) 18 img