mirror of
https://github.com/andre-wojtowicz/uci-ml-to-r.git
synced 2024-07-22 07:35:30 +02:00
88 lines
2.4 KiB
Plaintext
88 lines
2.4 KiB
Plaintext
---
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title: "UCI Machine Learning datasets for R"
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author: "Andrzej Wójtowicz"
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output:
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html_document:
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keep_md: yes
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---
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```{r global-options, include=FALSE}
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knitr::opts_chunk$set(comment="", echo=FALSE,
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warning=FALSE, message=FALSE)
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source('config.R')
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```
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Document generation date: `r Sys.time()`.
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```{r show-datasets, results='asis'}
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library(yaml)
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cat("\n# Table of Contents\n\n")
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for (dir.name in dir(PATH_DATASETS))
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{
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config.yaml.file.path = paste0(PATH_DATASETS, dir.name, "/", FILE_CONFIG_YAML)
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config.yaml = yaml.load_file(config.yaml.file.path)
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anchor = gsub(" ", "-", gsub("[[:punct:]]", "",
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tolower(config.yaml$name)))
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cat(paste0("1. [", config.yaml$name, "](#", anchor, ")\n" ))
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}
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cat("\n---\n\n")
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for (dir.name in dir(PATH_DATASETS))
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{
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config.yaml.file.path = paste0(PATH_DATASETS, dir.name, "/", FILE_CONFIG_YAML)
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config.yaml = yaml.load_file(config.yaml.file.path)
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cat(paste("#", config.yaml$name, "\n\n"))
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cat(paste("**Local directory**:", dir.name, "\n\n"))
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cat(paste0("**Details**: [link](", config.yaml$info, ")\n\n"))
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cat(paste("**Files**:\n\n"))
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for (file.url in config.yaml$urls)
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{
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cat(paste0("* [", URLdecode(basename(file.url)), "](", file.url, ")\n"))
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}
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cat("\n")
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cat(paste0("**Cite**:\n```nohighlight\n", config.yaml$cite, "\n```\n\n"))
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cat(paste("**Dataset**:\n\n"))
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preprocessed.dir = gsub("\\*", dir.name, PATH_DATASET_PREPROCESSED)
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preprocessed.file.path = paste0(preprocessed.dir, FILE_PREPROCESSED_OUTPUT)
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dataset = readRDS(preprocessed.file.path)
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cat("```nohighlight\n")
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cat(str(dataset))
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cat("\n```\n\n")
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cat("**Predictors**:\n\n")
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df.pred = data.frame(table(sapply(dataset[, 1:(ncol(dataset)-1)],
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function(f){paste(class(f), collapse=" ")})))
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colnames(df.pred) = c("Class", "Frequency")
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cat(knitr::kable(df.pred, format="markdown"), sep="\n")
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cat("\n")
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perc.classes = sort(round(100*as.numeric(
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table(dataset[, ncol(dataset)]))/nrow(dataset), 0))
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num.classes = sort(as.numeric(table(dataset[, ncol(dataset)])))
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cat(paste("**Class imbalance**:",
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paste0(perc.classes[1], "% / ",
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perc.classes[2], "% (",
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num.classes[1], " / ",
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num.classes[2], ")\n\n")))
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cat("---\n\n")
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}
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```
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