# ipft 0.2.2

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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 ipfKnn This function implements the k-nearest neighbors algorithm ipfPlotEst Plots the estimated locations ipfPlotEcdf Plots the cumulative distribution function of the estimated error ipfPlotPdf Plots the probability density function of the estimated error ipfEstimate This function estimates the location of the test observations ipfProb This function implements a probabilistic algorithm ipfGroup Creates groups based on the specified parameters ipfPlotLoc Plots the spatial location of the observations ipfCluster Creates clusters using the specified method ipfDist Distance function ipfTransform Transform function ipftrain Indoor localization training data set to test Indoor Positioning System that ipftest Indoor localization test data set to test Indoor Positioning System that No Results!