##### 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 nu-SVC code

display(nu_svc_svm_classifier_hist_testing)

PredictMD.singlelabelbinaryclassificationmetrics(
    nu_svc_svm_classifier,
    smoted_training_features_df,
    smoted_training_labels_df,
    single_label_name,
    positive_class;
    sensitivity = 0.95,
    )

PredictMD.singlelabelbinaryclassificationmetrics(
    nu_svc_svm_classifier,
    testing_features_df,
    testing_labels_df,
    single_label_name,
    positive_class;
    sensitivity = 0.95,
    )

nu_svc_svm_classifier_filename = joinpath(
    PROJECT_OUTPUT_DIRECTORY,
    "nu_svc_svm_classifier.jld2",
    )

PredictMD.save_model(
    nu_svc_svm_classifier_filename,
    nu_svc_svm_classifier,
    )

### End nu-SVC code

##### End of file

This page was generated using Literate.jl.