411 search results for "PCA"

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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Autoencoders and anomaly detection with machine learning in fraud analytics

April 30, 2017
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Autoencoders and anomaly detection with machine learning in fraud analytics

All my previous posts on machine learning have dealt with supervised learning. But we can also use machine learning for unsupervised learning. The latter are e.g. used for clustering and (non-linear) dimensionality reduction. For this task, I am using...

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Microeconomic Theory and Linear Regression (Part 2)

April 21, 2017
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Microeconomic Theory and Linear Regression (Part 2)

Introduction In the first part of this article I explained and compared four different functional forms to model apples' production. This is what I need to retake the previously explained examples: # Libraries #install.packages(c("micEcon","lmtest","bbmle","miscTools")) library(micEcon) library(lmtest) library(stats4) #this is a base package so I don't install this library(bbmle) library(miscTools

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RcppQuantuccia 0.0.1

April 19, 2017
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New package! And, as it happens, a effectively a subset or variant of one my oldest packages, RQuantLib. Fairly recently, Peter Caspers started to put together a header-only subset of QuantLib. He called this Quantuccia, and, upon me asking, said that it stands for "little sister" of QuantLib. Very nice. One design goal is to keep...

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Microeconomic Theory and Linear Regression (Part 1)

April 14, 2017
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Microeconomic Theory and Linear Regression (Part 1)

Introduction Last week I found a lot of materials I used as teaching assistant. Among those materials I found some class notes from Arne Henningsen, the author of micEcon R package. I'll use that package and some others to show some concepts from Microeconomic Theory. Packages installation: #install.packages(c("micEcon","lmtest","bbmle","miscTools")) library(micEcon) library(lmtest) library(stats4) #this is a...

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Microeconomic Theory and Linear Regression (Part 1)

April 14, 2017
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Microeconomic Theory and Linear Regression (Part 1)

Introduction Last week I found a lot of materials I used as teaching assistant. Among those materials I found some class notes from Arne Henningsen, the author of micEcon R package. I'll use that package and some others to show some concepts from Microeconomic Theory. Packages installation: #install.packages(c("micEcon","lmtest","bbmle","miscTools")) library(micEcon) library(lmtest) library(stats4) #this is a...

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Sakura blossoms in Japan

April 10, 2017
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Sakura blossoms in Japan

Springtime and cherry blossoms It is spring, and the flowers bloom. One tree in particular symbolises this: the Japanese cherry (sakura) tree. Every year, millions of Japanese enjoy hanami, jointly watching the cherry blossoms, philosophising abo...

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Web Scraping and Applied Clustering Global Happiness and Social Progress Index

April 9, 2017
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Web Scraping and Applied Clustering Global Happiness and Social Progress Index

Increasing amount of data is available on the web. Web scraping is a technique developed to extract data from web pages automatically and transforming it into a data format for further data analysis and insights. Applied clustering is an unsupervised learning technique that refers to a family of pattern discovery and data mining tools with Related Post

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Building meaningful machine learning models for disease prediction

March 30, 2017
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Building meaningful machine learning models for disease prediction

Webinar for the ISDS R Group This document presents the code I used to produce the example analysis and figures shown in my webinar on building meaningful machine learning models for disease prediction. My webinar slides are available on Github ...

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