In this article, I attempt to compare the results of the auto arima function with the ARIMA model we developed in the article Forecasting Time Series with ARIMA (https://www.alldatascience.com/time-series/forecasting-time-series-with-arima/). I made this attempt to see how it works and what the differences are.The parameters selected by auto-arima are slightly different than the ones selected by me in the other article.Auto arima has the advantage of attempting to find the best ARIMA parameters by comparing the
Seguir leyendoEtiqueta: open data
Forecasting time series with ARIMA
In this post, I’ll attempt to show how to forecast time series data using ARIMA (autoregressive integrated moving average). As usual, I try to practice with «real-world», which can be obtained easily by downloading open data from government websites. I chose the unemployment rate in the European Union’s 27 member countries. The data were obtained from the OECD data portal (http://dataportal.oecd.org/). First of all, I’m going to try to clean up the data, in this
Seguir leyendoComparing Data Augmentation Techniques to Deal with an Unbalanced Dataset (Pollution Levels Predictions)
Predicting NO2 levels in Madrid While looking for data to develop my data science skills, I came up with the idea of searching open data portals. I wanted to look at actual datasets and find out what they were like. For this purpose, I chose open data from the Madrid Open Data Portal (https://datos.madrid.es/portal/site/egob). I will try to predict NO2 concentration using weather and traffic data. This is not meant to be a definitive prediction
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