From 03462fc9a577e2dedd042961963eef31993068d1 Mon Sep 17 00:00:00 2001
From: ShusenTang <tangshusen@pku.edu.cn>
Date: Sun, 23 Feb 2020 12:32:51 +0800
Subject: [PATCH] :hammer: fix bug #97

---
 .../3.16_kaggle-house-price.ipynb             | 747 +++++++++---------
 .../3.16_kaggle-house-price.md                |  16 +-
 2 files changed, 371 insertions(+), 392 deletions(-)

diff --git a/code/chapter03_DL-basics/3.16_kaggle-house-price.ipynb b/code/chapter03_DL-basics/3.16_kaggle-house-price.ipynb
index bebe879..2c5c66a 100644
--- a/code/chapter03_DL-basics/3.16_kaggle-house-price.ipynb
+++ b/code/chapter03_DL-basics/3.16_kaggle-house-price.ipynb
@@ -298,7 +298,7 @@
     "    with torch.no_grad():\n",
     "        # 将小于1的值设成1，使得取对数时数值更稳定\n",
     "        clipped_preds = torch.max(net(features), torch.tensor(1.0))\n",
-    "        rmse = torch.sqrt(2 * loss(clipped_preds.log(), labels.log()).mean())\n",
+    "        rmse = torch.sqrt(loss(clipped_preds.log(), labels.log()))\n",
     "    return rmse.item()"
    ]
   },
@@ -405,12 +405,12 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "fold 0, train rmse 0.240939, valid rmse 0.221437\n",
-      "fold 1, train rmse 0.229326, valid rmse 0.267492\n",
-      "fold 2, train rmse 0.231815, valid rmse 0.237722\n",
-      "fold 3, train rmse 0.237550, valid rmse 0.219035\n",
-      "fold 4, train rmse 0.230578, valid rmse 0.258887\n",
-      "5-fold validation: avg train rmse 0.234042, avg valid rmse 0.240915\n"
+      "fold 0, train rmse 0.170585, valid rmse 0.156860\n",
+      "fold 1, train rmse 0.162552, valid rmse 0.190944\n",
+      "fold 2, train rmse 0.164199, valid rmse 0.168767\n",
+      "fold 3, train rmse 0.168698, valid rmse 0.154873\n",
+      "fold 4, train rmse 0.163213, valid rmse 0.183080\n",
+      "5-fold validation: avg train rmse 0.165849, avg valid rmse 0.170905\n"
      ]
     },
     {
@@ -450,10 +450,10 @@
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     "    preds = net(test_features).detach().numpy()\n",
     "    test_data['SalePrice'] = pd.Series(preds.reshape(1, -1)[0])\n",
     "    submission = pd.concat([test_data['Id'], test_data['SalePrice']], axis=1)\n",
-    "    submission.to_csv('./submission.csv', index=False)"
+    "    # submission.to_csv('./submission.csv', index=False)"
    ]
   },
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diff --git a/docs/chapter03_DL-basics/3.16_kaggle-house-price.md b/docs/chapter03_DL-basics/3.16_kaggle-house-price.md
index bdb8715..751d6d7 100644
--- a/docs/chapter03_DL-basics/3.16_kaggle-house-price.md
+++ b/docs/chapter03_DL-basics/3.16_kaggle-house-price.md
@@ -131,7 +131,7 @@ def log_rmse(net, features, labels):
     with torch.no_grad():
         # 将小于1的值设成1，使得取对数时数值更稳定
         clipped_preds = torch.max(net(features), torch.tensor(1.0))
-        rmse = torch.sqrt(2 * loss(clipped_preds.log(), labels.log()).mean())
+        rmse = torch.sqrt(loss(clipped_preds.log(), labels.log()))
     return rmse.item()
 ```
 
@@ -203,12 +203,12 @@ def k_fold(k, X_train, y_train, num_epochs,
 ```
 输出：
 ```
-fold 0, train rmse 0.241054, valid rmse 0.221462
-fold 1, train rmse 0.229857, valid rmse 0.268489
-fold 2, train rmse 0.231413, valid rmse 0.238157
-fold 3, train rmse 0.237733, valid rmse 0.218747
-fold 4, train rmse 0.230720, valid rmse 0.258712
-5-fold validation: avg train rmse 0.234155, avg valid rmse 0.241113
+fold 0, train rmse 0.170585, valid rmse 0.156860
+fold 1, train rmse 0.162552, valid rmse 0.190944
+fold 2, train rmse 0.164199, valid rmse 0.168767
+fold 3, train rmse 0.168698, valid rmse 0.154873
+fold 4, train rmse 0.163213, valid rmse 0.183080
+5-fold validation: avg train rmse 0.165849, avg valid rmse 0.170905
 ```
 <img width="400" src="../img/chapter03/3.16_output2.png"/>
 
@@ -250,7 +250,7 @@ train_and_pred(train_features, test_features, train_labels, test_data, num_epoch
 ```
 输出：
 ```
-train rmse 0.229943
+train rmse 0.162085
 ```
 <img width="400" src="../img/chapter03/3.16_output3.png"/>
 
-- 
GitLab