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You would like to attend the meeting but could not get a ticket? Follow the live event online! The post 7th MilanoR Meeting live on Facebook appeared first on MilanoR. [Read more...]

When performing some kind of analysis in R it is usually common to use data stored in basic formats such as .csv or .Rdata, and then present the analysis using a .Rmd file. Linpe package allows to send a single file instead of two. It has been created by Andrea ... [Read more...]

Quantide in partnership with DataCamp , offers an introductory online course to R completely in Italian. The course is free and open to anyone who wishes to participate. There is no requirement, you need only a Pc or a Mac with an Internet access. The post Introduction to R: free basic ... [Read more...]

Principal components regression (PCR) is a regression method based on Principal Component Analysis: discover how to perform this Data Mining technique in R The post Performing Principal Components Regression (PCR) in R appeared first on MilanoR. [Read more...]

A method to gather data from different sources, sort them and keep a reference to the origin of each subset, plus some efficiency considerations The post How to sort a list of dataframes appeared first on MilanoR. [Read more...]

A copula is a function which couples a multivariate distribution function to its marginal distribution functions, generally called marginals or simply margins. Copulas are great tools for modelling and simulating correlated random variables. The main appeal of copulas is that by using them you can model the correlation structure and ... [Read more...]

Missing data can be a not so trivial problem when analysing a dataset and accounting for it is usually not so straightforward either. If the amount of missing data is very small relatively to the size of the dataset, then leaving out the few samples with missing features may be ... [Read more...]

Neural networks have always been one of the most fascinating machine learning model in my opinion, not only because of the fancy backpropagation algorithm, but also because of their complexity (think of deep learning with many hidden layers) and structure inspired by the brain. Neural networks have not always been ... [Read more...]

Logistic regression is a method for fitting a regression curve, y = f(x), when y is a categorical variable. The typical use of this model is predicting y given a set of predictors x. The predictors can be continuous, categorical or a mix of both. The categorical variable y, in ... [Read more...]

A linear relationship between two variables x and y is one of the most common, effective and easy assumptions to make when trying to figure out their relationship. Sometimes however, the true underlying relationship is more complex than that, and this is when polynomial regression comes in to help. Let ... [Read more...]