Blog Archives

Dangerous streets of Bratislava! Animated maps using open data in R

November 9, 2019
By
Dangerous streets of Bratislava! Animated maps using open data in R

At the work recently, I wanted to make some interesting start-up pitch (presentation) ready animated visualization and got some first experience with spatial data (e.g. polygons). I enjoyed working with such a type of data and I wanted to improve on wo...

Read more »

Bootstrapping time series for improving forecasting accuracy

October 20, 2019
By
Bootstrapping time series for improving forecasting accuracy

Bootstrapping time series? It is meant in a way that we generate multiple new training data for statistical forecasting methods like ARIMA or triple exponential smoothing (Holt-Winters method etc.) to improve forecasting accuracy. It is called bootstra...

Read more »

Multiple Data (Time Series) Streams Clustering

February 2, 2019
By

Nowadays, data streams occur in many real scenarios. For example, they are generated from sensors, web traffic, satellites, and other interesting use cases. We have to process them in a fast way and extract from them as much knowledge as we can. Data s...

Read more »

My eRum 2018 biggest highlights

May 18, 2018
By
My eRum 2018 biggest highlights

On the range of dates 14.-16. May 2018, the European R users meeting (eRum) was held in Budapest. I was there as an active participant since I had the presentation about time series data mining. The eRum 2018 was a very successful event and I want to thank organizers of this event for a great organization of it. This blog...

Read more »

TSrepr use case – Clustering time series representations in R

March 12, 2018
By
TSrepr use case – Clustering time series representations in R

In the previous blog post, I showed you usage of my TSrepr package. There was shown what kind of time series representations are implemented and what are they good for. In this tutorial, I will show you one use case how to use time series representati...

Read more »

TSrepr – Time Series Representations in R

January 25, 2018
By
TSrepr – Time Series Representations in R

I’m happy to announce a new package that has recently appeared on CRAN, called “TSrepr” (version 1.0.0: https://CRAN.R-project.org/package=TSrepr). The TSrepr package contains methods of time series representations (dimensionality reduction, feature extraction or preprocessing) and several other useful helper methods and functions. Time series representation can be defined as follows: Let \( x \) be a time series of length \( n \),...

Read more »

Ensemble learning for time series forecasting in R

October 18, 2017
By
Ensemble learning for time series forecasting in R

Ensemble learning methods are widely used nowadays for its predictive performance improvement. Ensemble learning combines multiple predictions (forecasts) from one or multiple methods to overcome accuracy of simple prediction and to avoid possible over...

Read more »

Using regression trees for forecasting double-seasonal time series with trend in R

August 21, 2017
By
Using regression trees for forecasting double-seasonal time series with trend in R

After blogging break caused by writing research papers, I managed to secure time to write something new about time series forecasting. This time I want to share with you my experiences with seasonal-trend time series forecasting using simple regression trees. Classification and regression tree (or decision tree) is broadly used machine learning method for modeling. They are favorite because...

Read more »

R<-Slovakia meetup started to build community in Bratislava

March 25, 2017
By
R<-Slovakia meetup started to build community in Bratislava

On 22. March a first special R related meetup called R

Read more »

R<-Slovakia meetup started to build community in Bratislava

March 25, 2017
By
R<-Slovakia meetup started to build community in Bratislava

On 22. March a first special R related meetup called R

Read more »

Search R-bloggers

Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)