Data
3D_Estimation_using_RSSI_of_WLAN_dataset_complete

3D_Estimation_using_RSSI_of_WLAN_dataset_complete

active ARFF All rights are reserved to AI for Good aiforgood.itu.int Visibility: public Uploaded 21-01-2024 by Israel Campero Jurado
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3D Location Estimation using RSSI of WLAN dataset.The 3D Location Estimation Using RSSI of Wireless LAN challengeaims to develop an AI/ML-based localization algorithm that canaccurately estimate the position of a receiver based on RSS informationfrom surrounding radio transmitters including height information(enabling the estimation of the target's 3D location).

16 features

latitude (target)numeric54 unique values
0 missing
longitude (target)numeric54 unique values
0 missing
receiver_height (target)numeric3 unique values
0 missing
indexnumeric14400 unique values
0 missing
unixtimenumeric10800 unique values
0 missing
ssidnumeric4 unique values
0 missing
frequencynumeric4 unique values
0 missing
channelnumeric2 unique values
0 missing
rssinumeric26 unique values
0 missing
ap_latitudenumeric4 unique values
0 missing
ap_longitudenumeric4 unique values
0 missing
distance_to_ap1numeric4 unique values
0 missing
distance_to_ap2numeric4 unique values
0 missing
distance_to_ap3numeric4 unique values
0 missing
distance_to_ap4numeric4 unique values
0 missing
splitstring2 unique values
0 missing

19 properties

14400
Number of instances (rows) of the dataset.
16
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
15
Number of numeric attributes.
0
Number of nominal attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
Average class difference between consecutive instances.
93.75
Percentage of numeric attributes.
0
Number of attributes divided by the number of instances.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.

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