Changes between Version 3 and Version 4 of datavali

Timestamp:

Jun 28, 2011, 6:27:15 PM (13 years ago)

Author:

dennisw

Comment:

--

datavali

@@ -41 +41 @@
 }}}
 100 rows of missing coordinates. First of all, the impact of these missing values depend on the speed you traveled/measured with. If your first coordinate was at the NE point, and the last was at the SW point of Leiden, there is quite a large gap. (A side note: you should increase your measurement intervals if this happens)
-For large gaps like these, it's hard to calculate an expected route. Even if within these missing values a random value would be measured (like a 10 missing/1 valid ratio), it might be wise to just ignore these values since it's hard to get a correct route on long distances.
+For large gaps like these, it's hard to calculate an expected route. Even if within these missing values a random value would be measured (like a 10 invalid/1 valid ratio), it might be wise to just ignore these invalid values since it's hard to get a correct route on long distances.
+You could import the valid values since it's a waste to throw them away. You have to ask yourself if these seemingly valid values -are- valid. If 1 in 11 is valid, your equipment might be broken, or some other problem could be there. In this case, these 'valid' values might be invalid after all.
 
 Say we still have these 100 missing rows, but your first coordinate is at the start of a street, and the last at the end of that same street. This is more likely to occur when you measure at fair intervals. In this case, it can't hurt to calculate the estimated route. However, if the street has an 'L' shape which you followed, coordinates are likely to intersect with houses and such.
@@ -57 +58 @@
 -50, 50%
 }}}
-Again, it might be wise to calculate an average to replace the invalid values. But say, someone else measures the same accespoint around the same location, and he receives valid values. Our average would be 45%, but he get's a 90%, or maybe a 5%.
+Again, it might be wise to calculate an average to replace the invalid values. But say, someone else measures the same accespoint around the same location, and he receives valid values.
 For this, it might be better to look at the history of the accespoint (assuming there is one, if not, there probably will be one in time). You could take the most recent dbms measured at around the same location:
 {{{
@@ -65 +66 @@
 -60, 40%
 }}}
-The first and third value don't show a lot of difference, so it should be fairly safe to take the old second value, and use it for the new measurement.
+The first and third value don't show a lot of difference between the old an new measurements, so it should be fairly safe to take the old second value, and use it for the new measurement.
 
 == Invalid SSID/BSSID ==