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Analyzing rtweet data with kerasformula

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Overview The kerasformula package offers a high-level interface for the R interface to Keras. It’s main interface is the kms function, a regression-style interface to keras_model_sequential that uses formulas and sparse matrices. The kerasformula package is available on CRAN, and can be installed with: # install the kerasformula package install.packages(“kerasformula”) # or devtools::install_github(“rdrr1990/kerasformula”) library(kerasformula) # install the core keras library (if you haven’t already done so) # see ?install_keras() for options e.g. install_keras(tensorflow = “gpu”) install_keras() The kms() function Many classic machine learning tutorials assume that data come in a relatively homogenous form (e.g., pixels for digit recognition or word counts or ranks) which can make coding somewhat cumbersome when data is contained in a heterogenous data frame. kms() takes advantage of the flexibility of R formulas to smooth this process. kms builds dense neural nets and, after fitting them,…
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