Merge pull request #21 from wengJJ/master

DAY 2 更新 DAY 7 修改及上传

Code/Day 11 K-NN.md

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+# K近邻法 (K-NN)
+
+<p align="center">
+  <img src="https://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Info-graphs/Day%207.jpg">
+</p>
+
+## 数据集 | 社交网络
+
+<p align="center">
+  <img src="https://github.com/Avik-Jain/100-Days-Of-ML-Code/blob/master/Other%20Docs/data.PNG">
+</p> 
+
+
+## 导入相关库
+```python
+import numpy as np
+import matplotlib.pyplot as plt
+import pandas as pd
+```
+
+## 导入数据集
+```python
+dataset = pd.read_csv('Social_Network_Ads.csv')
+X = dataset.iloc[:, [2, 3]].values
+y = dataset.iloc[:, 4].values
+```
+
+## 将数据划分成训练集和测试集
+```python
+from sklearn.cross_validation import train_test_split
+X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.25, random_state = 0)
+```
+## 特征缩放
+```python
+from sklearn.preprocessing import StandardScaler
+sc = StandardScaler()
+X_train = sc.fit_transform(X_train)
+X_test = sc.transform(X_test)
+```
+## 使用K-NN对训练集数据进行训练
+```python
+from sklearn.neighbors import KNeighborsClassifier
+classifier = KNeighborsClassifier(n_neighbors = 5, metric = 'minkowski', p = 2)
+classifier.fit(X_train, y_train)
+```
+## 对测试集进行预测
+```python
+y_pred = classifier.predict(X_test)
+```
+
+## 生成混淆矩阵
+```python
+from sklearn.metrics import confusion_matrix
+cm = confusion_matrix(y_test, y_pred)
+```