Author: Learning Machines

Feed: R-bloggers. Author: Learning Machines. The global lockdown has slowed down mobility considerably. This can be seen in the data produced by our ubiquitous mobile phones. Apple is kind enough to make those anonymized and aggregated data available to the public. If you want to learn how to get a handle on those data and analyze trends with R read on! To download the current data set go to the following website, click on “All Data CSV”: Apple Maps: Mobility Trends Reports and move the file to your data folder. Apple explains: The CSV file and charts on this site ... Read More

Feed: R-bloggers. Author: Learning Machines. One widely used graphical plot to assess the quality of a machine learning classifier or the accuracy of a medical test is the Receiver Operating Characteristic curve, or ROC curve. If you want to gain an intuition and see how they can be easily created with base R read on! Many machine learning classifiers give you some kind of score or probability of the predicted class. One example is logistic regression (see also Learning Data Science: The Supermarket knows you are pregnant before your Dad does). If we had a perfect (binary) classifier the true ... Read More

Feed: R-bloggers. Author: Learning Machines. One of the biggest problems of the COVID-19 pandemic is that there are no reliable numbers of infections. This fact renders many model projections next to useless. If you want to get to know a simple method how to roughly estimate the real number of infections and expected deaths in the US, read on! As we have seen many times on this blog: simple doesn’t always mean inferior, it only means more comprehensible! The following estimation is based on a simple idea from an article in DER SPIEGEL (H. Dambeck: Was uns die Zahl der ... Read More

Feed: R-bloggers. Author: Learning Machines. Learning Machines proudly presents a guest post by Martijn Weterings from the Food and Natural Products research group of the Institute of Life Technologies at the University of Applied Sciences of Western Switzerland in Sion. The topic of this post will be the fitting with the R-package optim. Food? That sounds like a rather unlikely match for writing a post on a blog about quantitative analysis, however, there is a surprising overlap between these disciplinary fields. For example, whether you model the transport of a flavour molecule or transport of a virus, the type of ... Read More

Feed: R-bloggers. Author: Learning Machines. Correlation and its associated challenges don’t lose their fascination: most people know that correlation doesn’t imply causation, not many people know that the opposite is also true (see: Causation doesn’t imply Correlation either) and some know that correlation can just be random (so-called spurious correlation). If you want to learn about a paradoxical effect nearly nobody is aware of, where correlation between two uncorrelated random variables is introduced just by sampling, read on! Let us just get into an example (inspired by When Correlation Is Not Causation, But Something Much More Screwy): for all intents ... Read More

Feed: R-bloggers. Author: Learning Machines. It is such a beautiful day outside, lot’s of sunshine, spring at last… and we are now basically all grounded and sitting here, waiting to get sick. So, why not a post from the new epicentre of the global COVID-19 pandemic, Central Europe, more exactly where I live: Germany?! Indeed, if you want to find out what the numbers tell us how things might develop here, read on! We will use the same model we already used in this post: Epidemiology: How contagious is Novel Coronavirus (2019-nCoV)?. You can find all the details there and ... Read More

Feed: R-bloggers. Author: Learning Machines. Valentine’s Day is around the corner and love is in the air… but, shock horror, nearly every second marriage ends in a divorce! Unfortunately, I can tell you first hand that this is an experience you’d rather not have. In this post, we see how data science, in the form of the OneR package and an interesting new data set, might potentially help you to avoid that tragedy… so read on! In a scientific study last year in Turkey, nearly 200 participants (married as well as divorced) were being asked to rate how important they ... Read More

Feed: R-bloggers. Author: Learning Machines. A new invisible enemy, only 30kb in size, has emerged and is on a killing spree around the world: 2019-nCoV, the Novel Coronavirus! It has already killed more people than the SARS pandemic and its outbreak has been declared a Public Health Emergency of International Concern (PHEIC) by the World Health Organization (WHO). If you want to learn how epidemiologists estimate how contagious a new virus is and how to do it in R read on! There are many epidemiological models around, we will use one of the simplest here, the so-called SIR model. We ... Read More

Feed: R-bloggers. Author: Learning Machines. We have all watched with great horror the catastrophic fires in Australia. Over many years scientists have been studying simulations to understand the underlying dynamics better. They tell us, that “what Australia needs is more fires, but of the right kind”. What do they mean by that? One such simulation of fire is based on Multi-Agent Systems (MAS), also called Agent-Based Modelling (ABM). An excellent piece of free software (and in fact the de facto standard) is NetLogo. Even better is that NetLogo can be fully controlled by R… and we will use this feature ... Read More

Feed: R-bloggers. Author: Learning Machines. We already covered the so-called Accuracy-Interpretability Trade-Off which states that oftentimes the more accurate the results of an AI are the harder it is to interpret how it arrived at its conclusions (see also: Learning Data Science: Predicting Income Brackets). This is especially true for Neural Networks: while often delivering outstanding results, they are basically black boxes and notoriously hard to interpret (see also: Understanding the Magic of Neural Networks). There is a new hot area of research to make black-box models interpretable, called Explainable Artificial Intelligence (XAI), if you want to gain some intuition ... Read More