alex/temperature-based-fertility-prediction-thesis
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Alex
2025-09-10 10:37:55 +02:00
parent 36901c736d
commit c78a68de80
199 changed files with 3561 additions and 22579 deletions
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code/experiment_setup.py
+79 -5
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@@ -14,31 +14,26 @@ def get_eval_functions(model_configuration: dict):
eval_functions = [
{
"name": "mean_absolute_error_overall",
"input_index": 0,
"eval_fn": sklearn.metrics.mean_absolute_error,
"accumulation_fn": np.mean,
},
{
"name": "mean_absolute_error_pre_ov",
"input_index": 0,
"eval_fn": pre_ov_error,
"accumulation_fn": np.mean,
},
{
"name": "mean_absolute_error_after_ov",
"input_index": 0,
"eval_fn": after_ov_error,
"accumulation_fn": np.mean,
},
{
"name": "mean_absolute_error_ov_in_days",
"input_index": 0,
"eval_fn": partial(ov_error, model_configuration=model_configuration),
"accumulation_fn": np.mean,
},
{
"name": "mean_absolute_error_five_days_before_ov",
"input_index": 0,
"eval_fn": partial(day_relative_to_ov_error,
day_relative_to_ov=-5,
model_configuration=model_configuration),
@@ -46,3 +41,82 @@ def get_eval_functions(model_configuration: dict):
}
]
return eval_functions
def get_fertility_based_eval_functions(model_configuration: dict):
eval_functions = [
{
"name": "mae_ov_over",
"eval_fn": sklearn.metrics.mean_absolute_error,
"accumulation_fn": np.mean,
"input_index": 1
},
{
"name": "mae_ov_over_before_ov",
"eval_fn": partial(get_ov_over_pre_ov_error, error_fn=sklearn.metrics.mean_absolute_error),
"accumulation_fn": np.mean,
"input_index": 1
},
{
"name": "mae_ov_over_after_ov",
"eval_fn": partial(get_ov_over_post_ov_error, error_fn=sklearn.metrics.mean_absolute_error),
"accumulation_fn": np.mean,
"input_index": 1
},
{
"name": "mse_ov_over",
"eval_fn": sklearn.metrics.mean_squared_error,
"accumulation_fn": np.mean,
"input_index": 1
},
{
"name": "mse_ov_over_before_ov",
"eval_fn": partial(get_ov_over_pre_ov_error, error_fn=sklearn.metrics.mean_squared_error),
"accumulation_fn": np.mean,
"input_index": 1
},
{
"name": "mse_ov_over_after_ov",
"eval_fn": partial(get_ov_over_post_ov_error, error_fn=sklearn.metrics.mean_squared_error),
"accumulation_fn": np.mean,
"input_index": 1
},
{
"name": "mae_fertility",
"eval_fn": sklearn.metrics.mean_absolute_error,
"accumulation_fn": np.mean,
"input_index": 0
},
{
"name": "mae_during_fertility",
"eval_fn": partial(get_during_fertility_error, error_fn=sklearn.metrics.mean_absolute_error),
"accumulation_fn": np.mean,
"input_index": 0
},
{
"name": "mae_non_fertility",
"eval_fn": partial(get_non_fertility_error, error_fn=sklearn.metrics.mean_absolute_error),
"accumulation_fn": np.mean,
"input_index": 0
},
{
"name": "mse_fertility",
"eval_fn": sklearn.metrics.mean_squared_error,
"accumulation_fn": np.mean,
"input_index": 0
},
{
"name": "mse_during_fertility",
"eval_fn": partial(get_during_fertility_error, error_fn=sklearn.metrics.mean_squared_error),
"accumulation_fn": np.mean,
"input_index": 0
},
{
"name": "mse_non_fertility",
"eval_fn": partial(get_non_fertility_error, error_fn=sklearn.metrics.mean_squared_error),
"accumulation_fn": np.mean,
"input_index": 0
},
]
return eval_functions