Selection for assessment split {{assessment_split}} - label {{label}}

In the table below, the performance for each hyperparameter setting (combination of preprocessing (if any), encoding and ML model) on each of validation split is shown along with the average performance for the optimization metric (if applicable). The hyperparameter setting chosen as optimal (the best average performance) is shown in bold.

{{#show_average}} {{/show_average}} {{#splits}} {{/splits}} {{#hp_settings}} {{#hp_splits}} {{/hp_splits}} {{#show_average}} {{/show_average}} {{/hp_settings}}
Hyperparameter settings (preprocessing, encoding, ML method) Performance ({{optimization_metric}})Average
Split {{split_index}}
{{#optimal}}{{/optimal}} {{hp_setting}} {{#optimal}}{{/optimal}} {{optimization_metric_val}} {{#optimal}}{{/optimal}} {{average}} {{#optimal}}{{/optimal}}

If the selection strategy was set to random (randomly split to training and validation datasets) and training percentage was set to 1 (meaning that all data will be used for training), the performance in the table above will not be computed, since no validation data will be available.

{{#has_other_metrics}}

The tables below show the performance for each hyperparameter setting across selection splits for different metrics which were not used for optimization.

{{#metrics}}

{{metric}}

{{{performance}}}
{{/metrics}} {{/has_other_metrics}} {{#has_data_split_reports}}

Reports on training and validation datasets

The reports below are obtained from the datasets after they were split to training and validation datasets for each of the splits, before any preprocessing, encoding or model training.

{{#data_split_reports}}

Split {{split_index}}

{{#train}}

Report {{name}} (training): {{info}}

{{#output_figures}}
{{#is_embed}} {{/is_embed}} {{^is_embed}} {{/is_embed}} {{#name}}

{{name}} (training data)

{{/name}}
{{/output_figures}}
{{/train}} {{#test}}

Report {{name}} (validation): {{info}}

{{#output_figures}}
{{#is_embed}} {{/is_embed}} {{^is_embed}} {{/is_embed}} {{#name}}

{{name}} (validation data)

{{/name}}
{{/output_figures}}
{{/test}} {{/data_split_reports}}
{{/has_data_split_reports}} {{#has_reports_per_setting}}

Reports per hyperparameter setting

The reports below are obtained for each split to training and validation datasets separately, after encoding or training a machine learning model, as noted below.

{{#reports_per_setting}}

Hyperparameter setting: {{hp_setting}}


{{#reports}}

Split {{split_index}}

{{#has_encoding_train_reports}}
Encoded training data reports
{{/has_encoding_train_reports}} {{#encoding_train_reports}}

Report {{name}} (training): {{info}}

{{#output_figures}}
{{#is_embed}} {{/is_embed}} {{^is_embed}} {{/is_embed}}

{{name}}

{{/output_figures}} {{/encoding_train_reports}} {{#has_encoding_test_reports}}
Encoded validation data reports
{{/has_encoding_test_reports}} {{#encoding_test_reports}}

Report {{name}} (validation): {{info}}

{{#output_figures}}
{{#is_embed}} {{/is_embed}} {{^is_embed}} {{/is_embed}}

{{name}}

{{/output_figures}} {{/encoding_test_reports}} {{#has_ml_reports}}
ML model reports
{{/has_ml_reports}} {{#ml_reports}}

Report {{name}}: {{info}}

{{#output_figures}}
{{#is_embed}} {{/is_embed}} {{^is_embed}} {{/is_embed}}

{{name}}

{{/output_figures}}
{{/ml_reports}} {{/reports}}
{{/reports_per_setting}} {{/has_reports_per_setting}}