tidymodels / parsnip
Files Coverage
aaa.R 0.00%
aaa_models.R 68.49%
aaa_multi_predict.R 70.00%
aaa_spark_helpers.R 0.00%
add_in.R 0.00%
adds.R 100.00%
arguments.R 89.90%
augment.R 100.00%
bag_mars.R 0.00%
bag_tree.R 0.00%
bart.R 0.00%
boost_tree.R 89.93%
c5_rules.R 0.00%
contr_one_hot.R 52.94%
control_parsnip.R 36.36%
convert_data.R 93.44%
cubist_rules.R 0.00%
decision_tree.R 60.23%
descriptors.R 56.52%
discrim_flexible.R 0.00%
discrim_linear.R 0.00%
discrim_quad.R 0.00%
discrim_regularized.R 0.00%
engines.R 89.80%
extract.R 100.00%
fit.R 80.46%
fit_helpers.R 96.36%
gen_additive_mod.R 32.56%
linear_reg.R 46.23%
logistic_reg.R 39.75%
mars.R 76.19%
misc.R 45.96%
mlp.R 84.24%
multinom_reg.R 33.93%
naive_Bayes.R 0.00%
nearest_neighbor.R 85.37%
nullmodel.R 61.02%
pls.R 0.00%
poisson_reg.R 0.00%
predict.R 64.54%
predict_class.R 68.18%
predict_classprob.R 75.00%
predict_hazard.R 0.00%
predict_interval.R 82.35%
predict_linear_pred.R 0.00%
predict_numeric.R 77.27%
predict_quantile.R 80.00%
predict_raw.R 0.00%
predict_survival.R 0.00%
predict_time.R 0.00%
proportional_hazards.R 76.09%
rand_forest.R 81.71%
rand_forest_data.R 82.98%
repair_call.R 0.00%
req_pkgs.R 88.24%
rule_fit.R 0.00%
surv_reg.R 47.30%
survival_reg.R 58.33%
svm_linear.R 87.67%
svm_poly.R 86.57%
svm_rbf.R 81.82%
tidy.R 50.00%
tidy_glmnet.R 0.00%
tidy_liblinear.R 100.00%
translate.R 91.67%
type_sum.R 0.00%
varying.R 55.22%
Folder Totals (67 files) 58.03%
Project Totals (67 files) 58.03%
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