testAssessment-class: testAssessment Class
In nlanderson9/languagePredictR: Predict Outcomes from Natural Language

testAssessment Class

call: The function called to generate this model, with all arguments specified by the user
data_text: The text input to test the model
data_outcome: The outcome variable input to test the model
type: Model type, "binary" or "continuous"
text: The name of the column in the test dataframe containing the data_text
outcome: The name of the column in the test dataframe containing the data_outcome
ngrams: The ngrams used to generate the tokens
dfmWeightScheme: The weight scheme used to create the document-frequency matrix
x: The document-frequency matrix
y: The dependent (outcome) variable
predicted_y: The predicted outcomes based on the model and test data
predicted_probabilities: (If binary) The predicted probabilities of the outcomes based on the model and test data
roc: (If binary) The ROC calculated using the predicted_y
roc_ci: (If binary) The boostrapped confidence interval calculated for the ROC
corr: (If continuous) The correlation using the predicted_y
level0: The bottom/first level of a binary variable, or the lowest value of a continuous variable
level1: The top/second level of a binary variable, or the highest value of a continuous variable
trainedModel: The name of the model used for the test
original_predictive_ngrams: The list of ngram predictors from the model
ngrams_present: The number of original_predictive_ngrams that appear in the test lanuage sample