Self-organizing maps are very useful for clustering and data visualization. Self-organizing maps (SOMs) are a form of neural network and a beautiful way to...
The post Self Organizing Maps in R- Supervised Vs Unsupervised appeared first on finnstats.
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Correlation Matrix Plots with corrmorrant
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Summary
In this post, a machine learning model is created using this week’s #TidyTuesday data set: CEO Departures. This data set contains descriptions of thousands of CEO departures and reasons for these departures. After filtering missing values fr...
[This article was first published on Shirin's playgRound, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your [Read more...]
Final results for the 2021 USMS ePostal National Championships have been posted. We’ll take a look at them using some basic summary stats and charts, then work up the data from inclusion in Shiny application built to present it interactively.
If you’d like to just skip to playing with ...
Below you’ll find the complete code and resources used to create the graphs in my talk The Good, the Bad and the Ugly: how to visualize Machine Learning data at this year’s Minds Mastering machines conference. You can find the German slides here:
You can find Part 1: The ...
Introduction
In the last decade, there have been spectacular advances on the practical side of machine learning.
One of the most impressive may be the success of Generative Adversarial Networks (GANs) for image generation (Goodfellow et al. 2014)....
This is the first part of our series about code performance in R. Let's assume you have written some code, it's working, it computes the results you need, but it is really slow. If you don't want to get slowed down in your work, y...
Timeseries analysis in R, in statistics time series, is one of the vast subjects, here we are going to analyze some basic functionalities with...
The post Timeseries analysis in R appeared first on finnstats.
Photo by Myriam Jessier on Unsplash
We recently teamed up with Extendo and ixpantia to learn how they use RStudio to help streamline their digital analytics offerings for more credible and durable marketing insights.
Extendo, known as MiWeb in the US, ...
There is an interesting challenge running on Kaggle at the moment. It has been designed in cooperation with the Coleridge Initiative (https://coleridgeinitiative.org/) . This initiative is established at the New York University, it’s goal is to facilitate data driven decision making by governments. In the challenge we get ...
Recently I had a spirited conversation with Victor Chernozhukov, a leading econometrician whose work spans both traditional subjects like panel data modeling and newer application of machine learning models to causal inference. While I admire his w... [Read more...]
Regression analysis in R, just look at the Boston housing data and we can see a total of 506 observations and 14 variables. In...
The post Regression analysis in R-Model Comparison appeared first on finnstats.
With ever increasing sources of movement data from GPS in phones, animal trackers, and other devices I want to learn about visualizing movement. This post explores a dataset of caribou tracker collar GPS data which can be found on figshare. The first step in any project is to prepare the ...
When we build Data Workflows and Machine Learning Pipelines, it is common to check for the existence of specific files ... Read moreHow to Check if a File or a Directory exists in R, Python and Bash
We’ve released the newest version of NIMBLE on CRAN and on our website. NIMBLE is a system for building and sharing analysis methods for statistical models, especially for hierarchical models and computationally-intensive methods (such as MCMC and SMC). Version 0.11.0 provides a variety of new functionality, improved error trapping, and ...
Handling missing values in R, one of the common tasks in data analysis is handling missing values. In R, missing values are often represented...
The post Handling missing values in R appeared first on finnstats.
The Tukey loss function The Tukey loss function, also known as Tukey’s biweight function, is a loss function that is used in robust statistics. Tukey’s loss is similar to Huber loss in that it demonstrates quadratic behavior near the origin. … Continue reading →
We have started a series of articles on tips and tricks for data scientists (mainly in Python and R). In ... Read more10 Tips And Tricks For Data Scientists Vol.6
Whether you hate or love it, Friends is one of the most popular sitcoms of all time, with over 50 million viewers at its peak.
The cast's characterizations were diverse enough for you to see a little bit of yourself and your friends in each of the characters as they stumbled ...