Publications by R on notast
Explaining Predictions: Random Forest Post-hoc Analysis (randomForestExplainer package)
Recap This is a continuation on the explanation of machine learning model predictions. Specifically, random forest models. We can depend on the random forest package itself to explain predictions based on impurity importance or permutation importance. Today, we will explore external packages which aid in explaining random forest predictions. Ext...
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Explaining Predictions: Boosted Trees Post-hoc Analysis (Xgboost)
Recap We’ve covered various approaches in explaining model predictions globally. Today we will learn about another model specific post hoc analysis. We will learn to understand the workings of gradient boosting predictions. Like past posts, the Clevaland heart dataset as well as tidymodels principle will be used. Refer to the first post of this...
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`R` you ready for python (gentle introduction to reticulate package)’
Just like how Thanos claimed to be inevitable in The Avengers, the direct or indirect use of python has become inevitable for R users in recent years. Fret not R users, you don’t have to abandon your favourite IDE, Rstudio, when using python. With the reticulate package you can use python in Rstudio and even have a mixture of R and python code ...
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What R you in python? (`R` vectors)
reticulate allows us to toggle between R and python in the same session, callling R objects when running python scripts and vice versa. When calling R data structures in python, the R structures are converted to the equivalent python structures where applicable. However, like translating English to Mandarin, translating R structures to python may...
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What `R` you? (R list in python)
Previously, we uncovered what are R vectors in python. In this post, we will convert R lists in python. A R list is a python … Like R vectors, it depends. A R list will behave differently in python depending if it is named or not. Unnamed R list An unnamed list in R is a python list but this does not mean R and python lists have the exact sam...
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What `R` you? (R matrixes and R arrays in python)
Recap Previously in this series, we discovered the equivalent python data structures of the following R data structures: vectors lists In this post, we will look at translating R arrays (and matrixes) into python. 1D R array A 1D R array prints like a vector. library(tidyverse) library(reticulate) py_run_string("import numpy as np") py_run_str...
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What `R` you? (R dataframe vs python dataframe)
Recap Previously in this series, we discovered the equivalent python data structures for the following R data structures: vectors lists arrays/matrixes In this post, we will look at translating R data frames into python. We will also compare and contrast data frames in R and python. R data frame is a python… Pretty straight forward, a R data...
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Predicting pneumonia outcomes: EDA part 1
Intro Data dictionary EDA blueprint Outcome Discard the noise 1 Other_ related category 2 Pt_ Patient related category Appropriate patients Case_number Age 3 R_ Radiology related category Effusion and effusion site On chest x-ray ( R_CXR_effusion, R_CXR_effusionSite) On CT chest (R_CT_effusion, R_CT_effusionSite) 4 SS_ Category related to sign...
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Predicting pneumonia outcomes: EDA part 2
Intro 9 Lab_ related category Missing Lab values Outlier Lab values High Lab_Hb levels Low Lab_Neu High Lab_Sugar 10 CS_ cultures related category 11 Abx_ antibiotics related category 11i Class of empirical antibiotics given 11ii Antibiotics given Number of antibiotics given 11iii Duration of antibiotics 12 Care_ continuum of care status categ...
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Predicting pneumonia outcomes: Feature Engineering
Intro 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 the assignment is to use DataRobot for predictive modelling. Exploratory data analysis and feature engineering will be done here in R before the data is imp...
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