Case: Analyzing Earthquakes

For our fourth case study, we put our hands on a data set of a survey concerning seismological data. The 10,333 measurements of earthquakes were taken between 1961 and 2002, each one tracking 10 attributes of the incident. Our aim is to indicate the most significant attributes that affect our target value, set as the magnitude of the earthquake. Table 1 gives you the names of these attributes.  

Table 1: Data set at a glance

Table 2 gives you further details on the target attribute. In other words, we attempted to extract patterns out of this data set, that interpret the behavior of each earthquake’s magnitude.

Table 2: Description of the target attribute

Some advanced filtering techniques returned us the following attributes as the most prominent ones, in terms of their information value, given the target.

 Table 3: Attributes of most informational value

With inputs like these, we put into use an extended set of advanced machine learning algorithms to finally bring to light patterns like the ones that follow:

Rule 1: if depth<=10km & year<=1964 then magnitude>6.5R (83% accuracy)

Rule 1 suggests with an accuracy of 83% that for seismic event before 1964, a depth of less than 10 km was expected to result a magnitude of more than 6.5 Richter.

Rule 2: If depth>19km  &  epicentery>=38.26km then Y=1 (89% accuracy)

Rule 2 indicates that when the epicenter of an earthquake is greater than 38.26km and its depth greater than 19 km, then, again, magnitude is expected to be greater than 6.5 Richter.

You may find a more extended description of the above, including a complete set of rules extracted, in the full case study report, which is available below (you may try the full screen view, or even download the .pdf of the document).

Now, if we could return such insights from a limited data set on a major and yet unsolved scientific problem, consider the power of our techniques applied in that data set of yours, yet remaining unused somewhere in your computer or in your intranet.

Still considering it? Learn more about our services here, we’re awaiting for your data, starting from now. 

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