h2. R wrapper for working with Google Prediction API

This package consists in a bunch of functions allowing the user to test Google Prediction API from R. It requires the user to have access to both Google Storage for Developers and Google Prediction API: see "here":http://code.google.com/apis/storage/ and "here":http://code.google.com/apis/predict/ for details.

Example usage:

#This example requires you had previously created a bucket named data_language on your Google Storage and you had uploaded a CSV file named language_id.txt (your data) into this bucket - see for details 
library(predictionapirwrapper)
## The first stage of using the API is to acquire an authorization token. This can be done via this command:
token <- GetAuthToken(email="[email protected]", passwd="mypassword")
## This command begins training on data that has been previously uploaded to Google Storage.
GoogleTrain(auth_token=token$Auth, mybucket="data_languages", mydata="language_id.txt")
## Once training has started, this command checks the status of the training job and gets meta-information on the model (if available).
GoogleTrainCheck(auth_token=token$Auth, mybucket="data_languages", mydata="language_id.txt")
## When training has finished, this command issues a request for a new prediction from the model. 
GooglePredict(auth_token=token$Auth, mybucket="data_languages", mydata="language_id.txt", myinput="La idioma mas fina")
## remove Trained Model
DeleteTrainedModel(auth_token=token$Auth, mybucket="data_languages", mydata="language_id.txt")

Copyright (c) 2010 Paolo Sonego

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