diff --git a/7.5/__pycache__/datas.cpython-312.pyc b/7.5/__pycache__/datas.cpython-312.pyc
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index 0000000000000000000000000000000000000000..94e8a20da37d1cf85acbce2cf61e8772d7907a2a
Binary files /dev/null and b/7.5/__pycache__/datas.cpython-312.pyc differ
diff --git a/7.5/datas.py b/7.5/datas.py
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index 0000000000000000000000000000000000000000..34a3b28b0e2eccaacb7684701bdbeb472eaf2468
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+++ b/7.5/datas.py
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+# 预测系统
+"""
+    数据格式
+    city: 城市
+    area: 面积
+    rooms: 室
+    school: 1 2 shi
+    style: 1  2  jing
+    price: 预测价格
+"""
+datas = [
+    {
+        "city": "太原",
+        "area": 100,
+        "rooms": 2,
+        "school": 1,
+        "style": 2,
+        "price": 8500
+    },
+    {
+        "city": "太原",
+        "area": 130,
+        "rooms": 3,
+        "school": 1,
+        "style": 2,
+        "price": 8700
+    },
+    {
+        "city": "太原",
+        "area": 120,
+        "rooms": 2,
+        "school": 2,
+        "style": 2,
+        "price": 8300
+    },
+    {
+        "city": "吕梁",
+        "area": 100,
+        "rooms": 2,
+        "school": 1,
+        "style": 2,
+        "price": 7000
+    },
+    {
+        "city": "吕梁",
+        "area": 130,
+        "rooms": 3,
+        "school": 1,
+        "style": 2,
+        "price": 7200
+    },
+    {
+        "city": "吕梁",
+        "area": 100,
+        "rooms": 2,
+        "school": 2,
+        "style": 2,
+        "price": 6900
+    },
+]
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diff --git a/7.5/predict.py b/7.5/predict.py
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index 0000000000000000000000000000000000000000..eb9bcc453b5123c3b21cb79690d4bb351a8e30ab
--- /dev/null
+++ b/7.5/predict.py
@@ -0,0 +1,33 @@
+import numpy as np
+# a = np.array([[1, 2, 3], [1, 2, 3], [1, 2, 3]])
+# b = np.array([1, 2, 3])
+# print(a)
+# print(a.T) 转置
+# print(a.dot(b))点乘
+# print(np.linalg.pinv(a)) 逆矩阵
+from datas import datas
+x = []
+y = []
+cityMark = {"吕梁": 1, "太原": 2}
+for item in datas:
+    single=[]
+    #城市
+    single.append(cityMark[item["city"]])
+    #面积
+    single.append(item["area"])
+    #房间数
+    single.append(item["rooms"])
+    #学区房
+    single.append(item["school"])
+    #装修
+    single.append(item["style"])
+    x.append(single)
+    y.append(item["price"])
+
+    x=np.array(x)
+    y=np.array(y)
+
+    theta=np.linalg.pinv(x.T.dot(x)).dot(x.T).dot(y)
+    print(theta.dot(np.array([2, 200, 2, 1, 1])))
+
+