##### Beginning of file
# This file was generated by PredictMD version 0.20.0
# For help, please visit https://www.predictmd.net
import PredictMD
### Begin project-specific settings
PredictMD.require_julia_version("v0.7.0")
PredictMD.require_predictmd_version("0.20.0")
# PredictMD.require_predictmd_version("0.20.0", "0.21.0-")
PROJECT_OUTPUT_DIRECTORY = PredictMD.project_directory(
homedir(),
"Desktop",
"breast_cancer_biopsy_example",
)
### End project-specific settings
### Begin Knet neural network classifier code
display(knet_mlp_classifier_hist_testing)
PredictMD.singlelabelbinaryclassificationmetrics(
knet_mlp_classifier,
smoted_training_features_df,
smoted_training_labels_df,
single_label_name,
positive_class;
sensitivity = 0.95,
)
PredictMD.singlelabelbinaryclassificationmetrics(
knet_mlp_classifier,
testing_features_df,
testing_labels_df,
single_label_name,
positive_class;
sensitivity = 0.95,
)
knet_mlp_classifier_filename = joinpath(
PROJECT_OUTPUT_DIRECTORY,
"knet_mlp_classifier.jld2",
)
PredictMD.save_model(knet_mlp_classifier_filename, knet_mlp_classifier)
### End Knet neural network classifier code
##### End of file
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