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opensv/data_shapley/solvers/improved_kernel_shap.py

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+from typing import Optional, Any
+
+import numpy as np
+from tqdm import trange
+from scipy.special import comb
+
+from opensv.utils.utils import get_utility
+
+Array = np.ndarray
+
+def improved_kernel_shap(
+        x_train: Array,
+        y_train: Array,
+        x_valid: Optional[Array] = None,
+        y_valid: Optional[Array] = None,
+        clf: Optional[Any] = None,
+        num_perm: int=500,
+) -> Array:   
+    N = len(y_train)
+    val = np.zeros(N)
+    idxes = list(range(N))
+    utilities = np.empty(num_perm)
+    coef = np.empty(num_perm)
+
+    coalitons = np.zeros((num_perm,N))
+    weight_list = np.array([1 / (cl * (N-cl)) for cl in range(1,N)])
+    coef_list = np.array([(N-1) / (comb(N,cl)* cl * (N-cl)) for cl in range(1,N)])
+
+    final_acc = get_utility(x_train, y_train, x_valid, y_valid, clf)
+    init_acc = get_utility([], [], x_valid, y_valid, clf )
+
+    for _ in range(num_perm/2):
+        np.random.shuffle(idxes)
+        i = np.random.choice(a=range(1, N), p=np.array(weight_list) / np.sum(weight_list))
+        x_temp, y_temp = x_train[idxes[:i], :], y_train[idxes[:i]]
+        utilities[2*_] = get_utility(x_temp, y_temp, x_valid, y_valid, clf)
+        coef[2*_] = coef_list[i-1]
+        coalitons[2*_,idxes[:i]] = 1
+        x_temp, y_temp = x_train[idxes[i:], :], y_train[idxes[i:]]
+        utilities[2*_+1] = get_utility(x_temp, y_temp, x_valid, y_valid, clf)
+        coef[2*_+1] = coef_list[i-1]
+        coalitons[2*_+1,idxes[i:]] = 1
+
+    A = np.einsum('ij,ik->jk', coalitons, coalitons) / (num_perm/2)
+    b = np.sum(coalitons * (utilities - init_acc)[:, np.newaxis], axis=0) / (num_perm/2)
+
+    Ainv = np.linalg.inv(A)
+    val = Ainv @ (b - np.ones(N)*(np.sum(Ainv @ b) - final_acc + init_acc)/np.sum(Ainv))
+    return val