368 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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In search of an incredible posterior

June 22, 2016
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In search of an incredible posterior

What is credibility? For over one hundred years 1 actuaries have been wresting with the idea of “credibility”. This is the process whereby one may make a quantitative assessment of the predictive power of sample data. Where necessary, the researcher augments the sample with some exogeneous information - usually more data - to arrive at a final conclusion. In...

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y-aware scaling in context

June 22, 2016
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Nina Zumel introduced y-aware scaling in her recent article Principal Components Regression, Pt. 2: Y-Aware Methods. I really encourage you to read the article and add the technique to your repertoire. The method combines well with other methods and can drive better predictive modeling results. From feedback I am not sure everybody noticed that in … Continue reading...

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Risk Models with Generalized PLS

June 12, 2016
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Risk Models with Generalized PLS

While developing risk models with hundreds of potential variables, we often run into the situation that risk characteristics or macro-economic indicators are highly correlated, namely multicollinearity. In such cases, we might have to drop variables with high VIFs or employ “variable shrinkage” methods, e.g. lasso or ridge, to suppress variables with colinearity. Feature extraction approaches

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Why you should read Nina Zumel’s 3 part series on principal components analysis and regression

June 9, 2016
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Why you should read Nina Zumel’s 3 part series on principal components analysis and regression

Short form: Win-Vector LLC’s Dr. Nina Zumel has a three part series on Principal Components Regression that we think is well worth your time. Part 1: the proper preparation of data (including scaling) and use of principal components analysis (particularly for supervised learning or regression). Part 2: the introduction of y-aware scaling to direct the … Continue reading...

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