cleanup evaluation functions

1 files changed, 2 insertions, 42 deletions

diff --git a/sec_certs/model/evaluation.py b/sec_certs/model/evaluation.py
index 0f3855a9..77c66ddf 100644
--- a/sec_certs/model/evaluation.py
+++ b/sec_certs/model/evaluation.py
@@ -1,29 +1,19 @@
 import json
 from pathlib import Path
 import logging
-from typing import Dict, List, Set, Optional, Union
+from typing import List, Set,Union
 
 import numpy as np
 
-from sec_certs.dataset.common_criteria import CCDataset
-from sec_certs.certificate.common_criteria import CommonCriteriaCert
-from sec_certs.dataset.cve import CVEDataset, CVE
-from sec_certs.serialization import CustomJSONEncoder
-import sec_certs.helpers as helpers
-import tqdm
-
 logger = logging.getLogger(__name__)
 
+
 def get_validation_dgsts(filepath: Union[str, Path]) -> Set[str]:
     with Path(filepath).open('r') as handle:
         data = json.load(handle)
     return set(data.keys())
 
 
-def get_y_true(certs: List[CommonCriteriaCert]) -> np.array:
-    return np.array([np.array([y.cve_id for y in cert.heuristics.related_cves]) if cert.heuristics.related_cves else np.array(['None']) for cert in certs], dtype='object')
-
-
 def compute_precision(y: np.array, y_pred: np.array, **kwargs):
     prec = []
     for true, pred in zip(y, y_pred):
@@ -41,33 +31,3 @@ def compute_precision(y: np.array, y_pred: np.array, **kwargs):
         else:
             prec.append(len(set_true.intersection(set_pred)) / len(set_true))
     return np.mean(prec)
-
-def cpe_evaluate_classifier(x_valid, y_pred, y_true, outpath):
-    precision = compute_precision(y_true, y_pred)
-
-    correctly_classified = []
-    badly_classified = []
-    n_new_certs_with_match = 0
-    n_newly_identified = 0
-
-    for (vendor, cert_name), predicted_cpes, verified_cpes in zip(x_valid, y_pred, y_true):
-        record = {'certificate_name': cert_name,
-                  'vendor': vendor,
-                  'heuristic version': helpers.compute_heuristics_version(cert_name),
-                  'predicted_cpes': list(predicted_cpes),
-                  'manually_assigned_cpes': list(verified_cpes)
-                  }
-        if set(verified_cpes).issubset(set(predicted_cpes)):
-            correctly_classified.append(record)
-        else:
-            badly_classified.append(record)
-
-        if len(verified_cpes) == 1 and len(predicted_cpes) > 1:
-            n_new_certs_with_match += 1
-        n_newly_identified += len(set(predicted_cpes) - set(verified_cpes))
-
-    results = {'Precision': precision, 'n_new_certs_with_match': n_new_certs_with_match, 'n_newly_identified': n_newly_identified, 'correctly_classified': correctly_classified, 'badly_classified': badly_classified}
-    print(f'While keeping precision: {precision}, the classifier identified {n_newly_identified} new CPE matches (Found match for {n_new_certs_with_match} certificates that were previously unmatched) compared to baseline.')
-
-    with Path(outpath).open('w') as handle:
-        json.dump(results, handle, indent=4)
\ No newline at end of file