# ipft v0.6

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## Indoor Positioning Fingerprinting Toolset

Algorithms and utility functions for indoor positioning using fingerprinting techniques. These functions are designed for manipulation of RSSI (Received Signal Strength Intensity) data sets, estimation of positions,comparison of the performance of different models, and graphical visualization of data. Machine learning algorithms and methods such as k-nearest neighbors or probabilistic fingerprinting are implemented in this package to perform analysis and estimations over RSSI data sets.

## Functions in ipft

 Name Description ipfGroup Creates groups based on the specified parameters ipfKnn Implements the k-nearest neighbors algorithm ipfCluster Creates clusters using the specified method ipfDist Distance function ipfPlotEcdf Plots the cumulative distribution function of the estimated error ipfPlotEst Plots the estimated locations ipfEstbp Estimates the positions of the access points ipfEstimate Estimates the location of the test observations ipfProb This function implements a probabilistic algorithm ipfProx Estimates the position of the observations from its fingerprints and the access point location ipftest Indoor localization test data set to test Indoor Positioning System that ipftrain Indoor localization training data set to test Indoor Positioning System that ipfPlotLoc Plots the spatial location of the observations ipfPlotPdf Plots the probability density function of the estimated error ipfTransform Transform function ipfpwap Indoor localization data set with the positions of the wireless access points present No Results!

## Details

 Type Package License GPL (>= 2) Encoding UTF-8 LazyData true RoxygenNote 6.0.1 LinkingTo Rcpp NeedsCompilation yes Packaged 2017-05-08 14:13:00 UTC; emilio Repository CRAN Date/Publication 2017-05-10 12:28:25 UTC
 imports apcluster , cluster , dplyr , ggplot2 , methods , Rcpp , stats depends R (>= 2.10) Contributors Emilio Sansano