Using themes in ggplot2
As noted elsewhere, sometimes beauty matters. A plot that’s pleasing to the eye will be considered more
gladly, and thus might be understood more thoroughly… Keep reading the original post at r-bloggers.comhttps://www.r-bloggers.com/using-themes-in-ggplot2/amp/?__twitter_impression=true
“PCA revisited” a nice post on PCA
Principal component analysis (PCA) is a dimensionality reduction technique which might come handy when building a predictive model or in the exploratory phase of your data analysis
Keep reading the original article at r-bloggers blog click here
R for GIS
In real estate, spatial data is the name of the game. Countless programs
in other domains utilize the power of this data, which is becoming more
prevalent by the day…
How to perform PCA with R? | R-bloggers
This post shows how to perform PCA with R and the package FactoMineR
If you want to learn more on methods such as PCA, you can enroll in this MOOC (everyting is free): MOOC on Exploratory Multivariate Data Analysis
Keep reading here
Principal Component Analysis in R | R-bloggers
Principal component analysis (PCA) is routinely employed on a wide range of problems. From the detection of outliers to predictive modeling, PCA has the ability of projecting the observations described by
p
variables into few orthogonal components defined at where the data ‘stretch’ the most, rendering a simplified overview.
Because k-Means Kluster! | R-bloggers
Cluster analysis is a form of unsupervised learning, which aims to group observations into clusters.
This ia a true classe on K-mean cluster Just Keep reading
Notas R 