340 search results for "pca"

PCA file calculation with "R".

December 5, 2011
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PCA file calculation with "R".

X es la matriz centrada (X is the centered matrix). Xcov es la matriz de covarianzas de X (Xcov is the covariance matrix of X).Con la función "eigen" calculamos los "eigenvectors" y "eigenvalues" de Xcov.(With the function "eigen" we calculate the "ei...

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Big-Data PCA: 50 years of stock data

June 17, 2011
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Big-Data PCA: 50 years of stock data

In this post, Revolution engineer Sherry LaMonica shows us how to use the RevoScaleR big-data package in Revolution R Enterprise to do principal components analysis on 50 years of stock market data -- ed. Principal components analysis, or PCA, seeks to find a set of orthogonal axes such that the first axis, or first principal component, accounts for as...

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Principal Component Analysis (PCA) vs Ordinary Least Squares (OLS): A Visual Explanation

September 16, 2010
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Principal Component Analysis (PCA) vs Ordinary Least Squares (OLS): A Visual Explanation

Over at stats.stackexchange.com recently, a really interesting question was raised about principal component analysis (PCA). The gist was “Thanks to my college class I can do the math, but what does it MEAN?” I felt like this a number of times in my life. Many of my classes were focused on the technical implementations they kinda

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Using R and r.mapcalc (GRASS) to Estimate Mean Topographic Curvature

August 3, 2010
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Using R and r.mapcalc (GRASS) to Estimate Mean Topographic Curvature

Recently I was re-reading a paper on predictive soil mapping (Park et al, 2001), and considered testing one of their proposed terrain attributes in GRASS. The attribute, originally described by Blaszczynski (1997), is the distance-weighted mean differe...

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Tutorial: Principal Components Analysis (PCA) in R

May 20, 2010
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Found this tutorial by Emily Mankin on how to do principal components analysis (PCA) using R. Has a nice example with R code and several good references. The example starts by doing the PCA manually, then uses R's built in prcomp() function to do the s...

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Compcache on Ubuntu on Amazon EC2

May 4, 2010
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Compcache on Ubuntu on Amazon EC2

The following fully-automatic Bash script downloads, compiles, and initializes compcache version 0.6.2 on Ubuntu Karmic Koala (9.10). This script creates two swaps with a maximum of 4GB uncompressed size each. Two swaps are used to take advantage of 2 CPUs (or CPU cores in a multicore CPU). Compcache is a fascinating memory compression system. The

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RcppParallel: Getting R and C++ to work (some more) in parallel

January 15, 2016
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RcppParallel: Getting R and C++ to work (some more) in parallel

(Post by Dirk Eddelbuettel and JJ Allaire) A common theme over the last few decades was that we could afford to simply sit back and let computer (hardware) engineers take care of increases in computing speed thanks to Moore’s law. That same line of thought now frequently points out that we are getting closer and closer

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Mini AI app using TensorFlow and Shiny

January 14, 2016
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Mini AI app using TensorFlow and Shiny

tr;dr Simple image recognition app using TensorFlow and Shiny About My weekend was full of deep learning and AI programming so as a milestone I made a simple image recognition app that: Takes an image input uploaded to Shiny UI Performs image recognition using TensorFlow Plots detected objects and scores in wordcloud App This app is to demonstrate powerful image recognition...

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Revolution R Open Performance Improvements

January 11, 2016
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Revolution R Open Performance Improvements

Since last year Revolution Analytics has been publishing beta versions of Revolution R Open and finally in April this year they released RRO 8.0.3. The current release is RRO 3.2.2 (naming was adapted to fit the R version it is built upon). This post will give you an introduction on my favorite new features, how The post

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Repel overlapping text labels in ggplot2

January 8, 2016
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Repel overlapping text labels in ggplot2

A while back I showed you how to make volcano plots in base R for visualizing gene expression results. This is just one of many genome-scale plots where you might want to show all individual results but highlight or call out important results by labeling them, for example, with a gene name. But if you want to annotate...

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