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updated readme
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README.md
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README.md
@ -3,7 +3,22 @@ Andrzej Wójtowicz
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Document generation date: 2016-07-17 02:31:21.
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Document generation date: 2016-07-17 02:59:19.
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This project preprocesses a few datasets from [UC Irvine Machine Learning
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Repository](https://archive.ics.uci.edu/ml/) into tidy R object files.
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It focuses on the binary classification datasets and saves only complete cases
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within a dataset.
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**R software**: [Microsoft R Open](https://mran.microsoft.com/open/) (3.2.5)
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**Reproducibility library**: [checkpoint](https://github.com/RevolutionAnalytics/checkpoint)
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**Reproducibility procedure**:
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1. Run *s1-download-data.R* to download original datasets.
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2. Run *s2-preprocess-data.R* to preprocess the datasets.
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3. Optionally knit s*3-make-readme.Rmd* to get an overview of the preprocessed datasets.
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# Table of Contents
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# Table of Contents
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@ -13,6 +13,21 @@ source('init.R')
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Document generation date: `r Sys.time()`.
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Document generation date: `r Sys.time()`.
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This project preprocesses a few datasets from [UC Irvine Machine Learning
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Repository](https://archive.ics.uci.edu/ml/) into tidy R object files.
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It focuses on the binary classification datasets and saves only complete cases
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within a dataset.
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**R software**: [Microsoft R Open](https://mran.microsoft.com/open/) (`r paste0(R.version$major, ".", R.version$minor)`)
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**Reproducibility library**: [checkpoint](https://github.com/RevolutionAnalytics/checkpoint)
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**Reproducibility procedure**:
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1. Run *s1-download-data.R* to download original datasets.
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2. Run *s2-preprocess-data.R* to preprocess the datasets.
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3. Optionally knit s*3-make-readme.Rmd* to get an overview of the preprocessed datasets.
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```{r show-datasets, results='asis'}
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```{r show-datasets, results='asis'}
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cat("\n# Table of Contents\n\n")
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cat("\n# Table of Contents\n\n")
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