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Add C param in constructor and creditcard dataset

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Ricardo Montañana Gómez
2020-05-14 10:48:39 +02:00
parent 8f71eeb316
commit e3ae3a3a6c
5 changed files with 465 additions and 73 deletions
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29
trees/Snode.py
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@@ -14,9 +14,9 @@ class Snode:
def __init__(self, clf: LinearSVC, X: np.ndarray, y: np.ndarray, title: str):
self._clf = clf
self._vector = None if clf is None else clf.coef_
self._interceptor = 0 if clf is None else clf.intercept_
self._interceptor = 0. if clf is None else clf.intercept_
self._title = title
self._belief = 0 # belief of the prediction in a leaf node based on samples
self._belief = 0. # belief of the prediction in a leaf node based on samples
self._X = X
self._y = y
self._down = None
@@ -45,21 +45,20 @@ class Snode:
if not self.is_leaf():
return
classes, card = np.unique(self._y, return_counts=True)
max_card = max(card)
min_card = min(card)
try:
self._belief = max_card / min_card
except:
self._belief = 0
self._class = classes[card == max_card]
if len(classes) > 1:
max_card = max(card)
min_card = min(card)
try:
self._belief = max_card / (max_card + min_card)
except:
self._belief = 0.
self._class = classes[card == max_card][0]
else:
self._belief = 1
self._class = classes[0]
def __str__(self) -> str:
if self.is_leaf():
num = 0
for i in np.unique(self._y):
num = max(num, self._y[self._y == i].shape[0])
den = self._y.shape[0]
accuracy = num / den if den != 0 else 1
return f"{self._title} LEAF accuracy={accuracy:.2f}, belief={self._belief:.2f} class={self._class}\n"
return f"Leaf class={self._class} belief={self._belief:.6f} counts={np.unique(self._y, return_counts=True)}\n"
else:
return f"{self._title}\n"