From f399ea62690f239e1ffd1d101edb18c4f058e45b Mon Sep 17 00:00:00 2001
From: cy <939601402@qq.com>
Date: Thu, 24 Oct 2024 17:27:44 +0800
Subject: [PATCH] =?UTF-8?q?=E6=9B=B4=E6=96=B0=20function.py?=
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---
 function.py | 12 ++++--------
 1 file changed, 4 insertions(+), 8 deletions(-)

diff --git a/function.py b/function.py
index a81f5b1..dc03465 100644
--- a/function.py
+++ b/function.py
@@ -43,14 +43,10 @@ def train_logreg(X, y, learning_rate=0.01, iterations=1000, batch_size=256):
     m, n = X.shape
     weights = np.zeros(n)
     for i in range(iterations):
-        for j in range(0, m, batch_size):
-            end = min(j + batch_size, m)
-            X_batch = X[j:end]
-            y_batch = y[j:end]
-            z = np.dot(X_batch, weights)
-            h = sigmoid(z)
-            gradient = np.dot(X_batch.T, (h - y_batch)) / len(X_batch)
-            weights -= learning_rate * gradient
+        z = np.dot(X, weights)
+        h = sigmoid(z)
+        gradient = np.dot(X.T, (h - y)) / m
+        weights -= learning_rate * gradient
     return weights
 
 def predict_logreg(inX, weights):