clf = LogisticRegressionCV(penalty='l2', Cs=10, cv=5) clf.fit(leaf_features_train, y_train) y_pred_prob = clf.predict_proba(leaf_features_test)[:, 1]

: Traditional relative relocations (like R_X86_64_RELATIVE ) require 24 bytes each on 64-bit systems. In large binaries with many global variables, these can take up significant disk space and memory. DT_RELR replaces these with a compact representation that can reduce the size of the relocation section by over 90% in some cases.

# Pseudo‑code for a custom dt_relr implementation from sklearn.tree import DecisionTreeClassifier from sklearn.linear_model import LogisticRegressionCV

Dt_relr ^new^ 95%

clf = LogisticRegressionCV(penalty='l2', Cs=10, cv=5) clf.fit(leaf_features_train, y_train) y_pred_prob = clf.predict_proba(leaf_features_test)[:, 1]

: Traditional relative relocations (like R_X86_64_RELATIVE ) require 24 bytes each on 64-bit systems. In large binaries with many global variables, these can take up significant disk space and memory. DT_RELR replaces these with a compact representation that can reduce the size of the relocation section by over 90% in some cases. dt_relr

# Pseudo‑code for a custom dt_relr implementation from sklearn.tree import DecisionTreeClassifier from sklearn.linear_model import LogisticRegressionCV clf = LogisticRegressionCV(penalty='l2', Cs=10, cv=5) clf