The goal of this challenge is to predict the NOx levels in the air in Northern Taiwan, which is an indicator of pollution. The dataset is from Kaggle and was initially provided by the Environmental Protection Administration, Executive Yuan, R.O.C.
(Taiwan). Data has been collected for several regions in Taiwan during one year using one hour sampling rate.For our analysis, we made the assumption that our features are independant.
A good way of evaluating the pollution rate is with the levels of NOx, a generic term for the nitrogen oxides, namely nitric oxide (NO) and nitrogen dioxide (NO2). These gases contribute to the formation of smog and acid rain, as well as tropospheric ozone.
Pollution, or the introduction of different forms of waste materials in our environment, has negative effects to the ecosystem we rely on. With modernization and development in our lives, pollution has reached its peak, giving rise to global warming and human illness.
In this project, we will focus on the air pollution in in northern Taiwan. Air Pollution is the most prominent and dangerous form of pollution. It occurs due to many reasons : excessive burning of fuel, driving and other industrial activities, etc.
The effects of air pollution are evident. Releasing hazardous gases into the air causes global warming and acid rains, which in turn increase temperatures, erratic rains and droughts worldwide, making it tough for animals to survive. We breathe in every polluted particle from the air : the result is an increased number of asthma cases and lung cancers.
It is interesting to note that 13% of diagnosed cancers worldwide in 2012 were lung cancers, a significant part being caused by air pollution.
Temperature Evolution since 1880
Air pollution in Taiwan is significantly created both domestically as well as blown over from China (People's Republic of China). Taiwan's topography has been noted to be a contributing factor to its air pollution problem. Taipei, Taiwan's capital and largest city for example, is surrounded by mountains, and other industrial centers along the northern and western coasts of Taiwan are surrounded by high mountains.
NOx represents a family of several compounds. In atmospheric chemistry, the term NOx means the total concentration of NO and NO2 . NO2 is not only an important air polluant by itself, but it also reacts in the atmosphere to form ozone (the ozone in the air we breathe, not stratospheric ozone) and acid rain.The European Union limit value is 40 micrograms per cubic meter ; this limit has been surpassed for the last decade. 
Ecolo Team : firstname.lastname@example.org
The competition protocol was designed by Isabelle Guyon.
This challenge was generated using ChaLab.
The problem is a regression problem ; the idea is to predict the levels of NOx. The dataset contains about70,000 examples for each of the training, validating and testing sets.
Each example is characterized by the following features :
In order to submit your results, go to "Participate", download the starting kit and follow the instructions. We also provide a submission example.
There are 2 phases:
This sample competition allows you to submit either:
The error we will use for the evaluation is the r-squared.
R-squared is a statistical measure of how close the data are to the fitted regression line. It is also known as the coefficient of determination, or the coefficient of multiple determination for multiple regression.
The definition of R-squared is fairly straight-forward; it is the percentage of the response variable variation that is explained by a linear model. Or:
R-squared = Explained variation / Total variation
R-squared is always between 0 and 1 :
In general, the higher the R-squared, the better the model fits your data.
Plotting fitted values by observed values graphically illustrates different R-squared values for regression models.
The regression model on the left accounts for 0.38 while the one on the right accounts for 0.87. The more variance that is accounted for by the regression model the closer the data points will fall to the fitted regression line. Theoretically, if a model could explain 100% of the variance, the fitted values would always equal the observed values and, therefore, all the data points would fall on the fitted regression line.
However, you need to be careful not to overfit your model. Overfitting a model is a condition where a statistical model begins to describe the random error in the data rather than the relationships between variables. This problem occurs when the model is too complex. Unfortunately, one of the symptoms of an overfit model is an R-squared value that is too high.
On the left : the blue line is underfitting the data ; the model has not been trained enough. Middle : a good model. Right : an overfitted model. While the model on the right best follows the training data, it is too dependent on that data and it is likely to have a higher error rate on new unseen data, compared to the one in the middle. (source)
Submissions must be made before the end of phase 1. You may submit 5 submissions every day and 100 in total.
This challenge is governed by the general ChaLearn contest rules.
This competition is organized solely for test purposes. No prizes will be awarded.
The authors decline responsibility for mistakes, incompleteness or lack of quality of the information provided in the challenge website. The authors are not responsible for any contents linked or referred to from the pages of this site, which are external to this site. The authors intended not to use any copyrighted material or, if not possible, to indicate the copyright of the respective object. The authors intended not to violate any patent rights or, if not possible, to indicate the patents of the respective objects. The payment of royalties or other fees for use of methods, which may be protected by patents, remains the responsibility of the users.
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Start: Oct. 22, 2017, 6:53 p.m.
Description: Development phase: create models and submit them or directly submit results on validation and/or test data; feed-back are provided on the validation set only.
Start: April 30, 2018, 6:53 p.m.
Description: Final phase: submissions from the previous phase are automatically cloned and used to compute the final score. The results on the test set will be revealed when the organizers make them available.
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