Predicting House Prices with the Ames Dataset
This problem is fairly simple to describe… given a bunch of variables that describe the various aspects of a house along with a sales price, is it possible to come up with a mathematical model that can be used to predict future prices based on different values of the same variables? It is based housing sales data …
Having fun with the Titanic Problem… Machine Learning from the Disaster
This is originally a Kaggle problem where the task is: to build a predictive model that answers the question: “what sorts of people were more likely to survive?” using passenger data (ie name, age, gender, socio-economic class, etc). The data is broken into train and test sets in a ratio of approximately 68 to 32 …
Looking at the SEIR Virus Model…
The SIR Model is a little basic and does not model Covid-19 very well. The SEIR model introduces extra parameters that can make the modelling a bit more accurate. The main change is the introduction of a new ‘exposed’ compartment, so we now have Susceptible, Exposed, Infected, and Recovered (or removed) compartments: There is a …
Solving the SIR Virus Model…
Due to the current covid-19 outbreak there has been a fair bit of interest in virus modelling lately. The models that the media have published/produced vary from the over simplified (and often incorrect) to the complex (with many missing details). I have already looked at numeric simulations using a bouncing ball model, this time a …