update comment for ch13

ch13_others/README.md

@@ -0,0 +1,11 @@
+
+|代码|说明|
+|---|---|
+|[dt_example.ipynb](dt_example.ipynb)| 决策树模型 |
+|[dt_logit.ipynb](dt_logit.ipynb)| 决策树与逻辑回归的联结，使用决策树来提取特征 |
+|[gbts.ipynb](gbts.ipynb)| 梯度提升决策树 |
+|[viterbipy.py](viterbipy.py)| viterbi算法的实现 |
+|[stock_analysis.ipynb](stock_analysis.ipynb)| 使用隐马尔可夫模型对A股数据进行分析 |
+|[kmeans.ipynb](kmeans.ipynb)| 聚类算法——KMeans |
+|[kmeans\_choose_k.ipynb](kmeans_choose_k.ipynb)| 如何选择聚类个数 |
+|[pca.ipynb](pca.ipynb)| 降维算法——主成分分析 |

ch13_others/kmeans.ipynb

@@ -112,7 +112,7 @@
     }
    ],
    "source": [
-    "# 创建一个图形框\n",
+    "# 展示模型步骤\n",
     "fig = plt.figure(figsize=(10, 10), dpi=80)\n",
     "for i in range(4):\n",
     "    ax = fig.add_subplot(2, 2, i+1)\n",

ch13_others/kmeans_choose_k.ipynb

@@ -88,7 +88,7 @@
     }
    ],
    "source": [
-    "# 创建一个图形框\n",
+    "# 展示聚类个数对结果的影响\n",
     "fig = plt.figure(figsize=(10, 10), dpi=80)\n",
     "sse = []\n",
     "for i in range(2, 6):\n",

ch13_others/pca.ipynb

@@ -49,6 +49,7 @@
     }
    ],
    "source": [
+    "# 主成分分析\n",
     "model = PCA(n_components=2)\n",
     "model.fit(data)"
    ]

ch13_others/stock_analysis.ipynb

@@ -6,6 +6,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "# 安装第三方库\n",
     "!pip install hmmlearn mplfinance"
    ]
   },
@@ -476,6 +477,7 @@
     }
    ],
    "source": [
+    "# 进行特征提取，得到5日和20日增长率\n",
     "data['a_5'] = np.log(data['amount']).diff(-5)\n",
     "data['a_20'] = np.log(data['amount']).diff(-20)\n",
     "data['r_5'] = np.log(data['close_price']).diff(-5)\n",
@@ -491,6 +493,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "# 使用隐马尔可夫模型对数据建模\n",
     "cols = ['r_5', 'r_20', 'a_5', 'a_20']\n",
     "model = GaussianHMM(n_components=3, covariance_type='full',\n",
     "                    n_iter=1000, random_state=1024)\n",
@@ -535,7 +538,7 @@
     }
    ],
    "source": [
-    "# 创建一个图形框\n",
+    "# 展示模型结果\n",
     "fig = plt.figure(figsize=(12, 8), dpi=80)\n",
     "ax0 = fig.add_subplot(4, 1, 1)\n",
     "draw_data(ax0, data)\n",