384 search results for "pca"

Choosing Software to Publish your Data Science Portfolio

January 23, 2017
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Choosing Software to Publish your Data Science Portfolio

I’ve recently spoken to several people who Have decided to create a portfolio of their data science projects Are new to online publishing They frequently have... The post Choosing Software to Publish your Data Science Portfolio appeared first on AriLamstein.com.

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Principal Component Analysis

January 19, 2017
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Principal Component Analysis

Often, it is not helpful or informative to only look at all the variables in a dataset for correlations or covariances. A preferable approach is to derive new variables from the original variables that preserve most of the information given by their variances. Principal component analysis is a widely used... The post Principal Component Analysis appeared first on...

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Feature Selection in Machine Learning (Breast Cancer Datasets)

January 14, 2017
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Feature Selection in Machine Learning (Breast Cancer Datasets)

Machine learning uses so called features (i.e. variables or attributes) to generate predictive models. Using a suitable combination of features is essential for obtaining high precision and accuracy. Because too many (unspecific) features pose the prob...

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R packages

December 12, 2016
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In this section, you’ll find R packages developed by STHDA for easy data analyses. factoextra factoextra let you extract and create ggplot2-based elegant visualizations of multivariate data analyse results, including PCA, CA, MCA, MFA, HMFA and clustering methods.

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The Wordcloud2 library

December 9, 2016
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The Wordcloud2 library

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Extreme Gradient Boosting and Preprocessing in Machine Learning – Addendum to predicting flu outcome with R

December 1, 2016
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Extreme Gradient Boosting and Preprocessing in Machine Learning – Addendum to predicting flu outcome with R

In last week’s post I explored whether machine learning models can be applied to predict flu deaths from the 2013 outbreak of influenza A H7N9 in China. There, I compared random forests, elastic-net regularized generalized linear models, k-nearest ne...

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Extract Twitter Data Automatically using Scheduler R package

November 29, 2016
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Extract Twitter Data Automatically using Scheduler R package

The following R-script is for download the data automatically from twitter using the package SchedulerR. As first step we download the data using the OAuth protocol and store the data using as a name the date from the download. As second we used the package SchedulerR for to specify how long the script runs. This Related Post

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How many Authors does the Prime Minister have for his speeches: A Stylometric Analysis

November 17, 2016
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How many Authors does the Prime Minister have for his speeches: A Stylometric Analysis

Some time back, an audio clip was broadcasted on a Pakistani television programme, purportedly of the Prime Minister of Pakistan, Nawaz Sharif, and his aides, who were discussing what to write in an important speech. The clip generated debate for few d...

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Rcmdr Plug-in(s)

November 15, 2016
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Rcmdr Plug-in(s)

These plug-ins enhance statistical graphical user interface by extending new menus to statistical package provided by Rcmdr. While the original GUI was created for a basic statistics calculations, enabling of extensions (or plug-ins) has greatly enhanced the possible use and scope of this software. Installing these plug-ins is quite easy. They can be installed like … Continue...

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Pipe-friendly workflow with sjPlot, sjmisc and sjstats, part 1 #rstats #tidyverse

November 14, 2016
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Pipe-friendly workflow with sjPlot, sjmisc and sjstats, part 1 #rstats #tidyverse

Recent development in R packages are increasingly focussing on the philosophy of tidy data and a common package design and api. Tidy data is an important part of data exploration and analysis, as shown in the following figure: Tidying data not only includes data cleaning, but also data transformation, both being necessary to perform the

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