https://blog.smarttechventures.au/tags/r-data-science/Recent content in R Data-Science on Chris McKelt - Remembering ThoughtsHugo -- 0.147.2enSun, 03 Dec 2017 00:00:00 +0800https://blog.smarttechventures.au/articles/posts/word-prediction-with-natural-language-processing/Sun, 03 Dec 2017 00:00:00 +0800https://blog.smarttechventures.au/articles/posts/word-prediction-with-natural-language-processing/<h3></h3> <p><a href="https://www.rpubs.com/chris_mckelt/capstone-presentation" target="_blank">https://www.rpubs.com/chris_mckelt/capstone-presentation</a></p>https://blog.smarttechventures.au/articles/posts/rdata-exploration/Sat, 23 Jul 2016 00:00:00 +0800https://blog.smarttechventures.au/articles/posts/rdata-exploration/<h1 id="pca">PCA</h1> <p><strong>Principal Components Analysis</strong> (PCA) allows us to study and explore a set of quantitative variables measured on a set of objects</p> <h6 id="core-idea">Core Idea</h6> <p> </p> <p>With PCA we seek to reduce the dimensionality (reduce the number of variables) of a data set while retaining as much as possible of the variation present in the data</p> <p>Before performing a PCA(or any other multivariate method) we should start with some preliminary explorations</p> <ul> <li>Descriptive statistics</li> <li>Basic graphical displays</li> <li>Distribution of variables</li> <li>Pair-wise correlations among variables</li> <li>Perhaps transforming some variables</li> <li>ETC</li> </ul> <p><img alt="image" loading="lazy" src="https://user-images.githubusercontent.com/662868/120943805-c6724780-c763-11eb-83bb-d1920d08269e.png"></p>