Introduction An example 6-state model Estimation Data Fitting Simulation mstate hesim Comparison ...
R news and tutorials contributed by hundreds of R bloggers
Introduction An example 6-state model Estimation Data Fitting Simulation mstate hesim Comparison ...
Today I want to predict churn using data from a hypothetical telecom company. Although it isn’t real life data, it is based on real life data. The data are spread across 19 columns — 14 continuous, 4 categorical, and the outcome variable for prediction - “churn”. The dataset is small, with 3333 rows for training and 1667 for testing. Before...
Introduction An example 6-state model Estimation Data Fitting Simulation mstate hesim Comparison ...
Introduction An example 6-state model Estimation Data Fitting Simulation mstate hesim Comparison ...
Here we go again, using a Twitter trend as blog fodder! Colin Fay launched an inspiring movement by sharing his R goals of 2019. My #RStats goals for 2019: 1️⃣ Becoming entirely fluent with {data.table}2️⃣ Getting at ease with {Rcpp} What are yours?#rdatatable #rcpp— Colin Fay 🤘 (@_ColinFay) December 29, 2018 It’s been quite interesting reading the objectives of other tweeps: what they...
RcppDynProg is a new Rcpp based R package that implements simple, but powerful, table-based dynamic programming. This package can be used to optimally solve the minimum cost partition into intervals problem (described below) and is useful in building piecewise estimates of functions (shown in this note). The abstract problem The primary problem RcppDynProg::solve_dynamic_program() is designed … Continue reading Introducing...
Well, 2018 has flown by and today seems like an appropriate time to take a look at the landscape of R bloggerdom as seen through the eyes of readers of R-bloggers and R Weekly. We’ll do this via a new package designed to make it easier to treat Feedly as a data source: seymour [GL... Continue reading →
CategoriesAdvanced Modeling Tags Linear Regression Principal Component Analysis R Programming In this post, I am going to build a statistical learning model as based upon plant leaf datasets introduced in part one of this tutorial. We have available three datasets, each one providing sixteen samples each of one-hundred plant species. The features are: shape texture margin Specifically, I will take advantage of Discrimination Analysis...
Here we are, ending yet another year and starting something new. I wanted to take a minute to dwell on 2018, what happened in my R world this year and reflexions I take from that. public speaking This year started for me with a bang - as a result of my presentation about LIME at one of H2O meetups (of which...
Giddy up, giddy it up Wanna move into a fool's gold room With my pulse on the animal jewels Of the rules that you choose to use to get loose With the luminous moves Bored of these limits, let me get, let me get it like Wow! When it comes to surreal lyrics and videos, I'm always thinking of Beck. Above, I cited the beginning of...
Jobs for R users