commit 13289dde6465f0d240d10d98d518d59720d392b1 Author: Frae19 <515745323@qq.com> Date: Thu Oct 31 17:01:24 2024 +0800 Initial commit diff --git a/.gitea/workflows/test.yaml b/.gitea/workflows/test.yaml new file mode 100644 index 0000000..6cb571f --- /dev/null +++ b/.gitea/workflows/test.yaml @@ -0,0 +1,27 @@ +name: Gitea Actions Experiment Test +run-name: 实验自动评测 Actions 🚀 +on: [push] + +jobs: + Experiment-Actions: + runs-on: ubuntu-latest + steps: + - name: 检出代码 + uses: actions/checkout@v4 + with: + fetch-depth: 0 + - name: 安装依赖 + run: | + python -m venv ./.venv + . ./.venv/bin/activate + curl -s -o pip_cache.tar.gz ${{ vars.BACKEND_URL }}/download/pip_cache.tar.gz + tar -zxf pip_cache.tar.gz + pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple + rm -rf horse-colic.data horse-colic.test main.py + curl -s -o main.py ${{ vars.BACKEND_URL }}/public/experiment/logreg/main.py + curl -s -o horse-colic.data ${{ vars.BACKEND_URL }}/public/experiment/logreg/horse-colic.data + curl -s -o horse-colic.test ${{ vars.BACKEND_URL }}/public/experiment/logreg/horse-colic.test + - name: 评测结果 + run: | + . ./.venv/bin/activate + python main.py diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..b415143 --- /dev/null +++ b/.gitignore @@ -0,0 +1,3 @@ +__pycache__ +main.py +病马数据集* diff --git a/README.md b/README.md new file mode 100644 index 0000000..2fcae54 --- /dev/null +++ b/README.md @@ -0,0 +1,60 @@ +# 实验二:对率回归与预测病马死亡 + +## 实验说明 + +- 自行在 [`function.py`](./function.py) 中编写实现数据加载与预测病马死亡的对率回归算法。 + +所有成功上传的评测结果均会被记录,但不会公开展示。 + +评测次数不限,最终评测成绩取**最高分**。 + +## 注意事项 + +挑战赛与实验为两个**不同**的仓库,注意不要混淆! + +- 实验仓库,开头名称统一为 `Experiment` + - **有截止时间限制**! + - 记录成绩但不公开,并且**是实验成绩的一部分**。 + - 最终成绩取最高分。 +- 挑战赛仓库,开头名称统一为 `Challenge` + - 无截止时间限制。 + - 公开展示排行榜和最近的评测信息。 + +--- + +实验开始前必须在 [`function.py`](./function.py#L28-L29) 中填写自己的学号和姓名! + +- 可以自行导入其他库,需要在 [`requirements.txt`](./requirements.txt) 添加依赖,若未在 [`requirements.txt`](./requirements.txt) 中添加使用到的依赖,则无法自动评测,**不记录成绩**。 +- 需要在 [`function.py`](./function.py) 中实现完整的对率回归算法。 +- 若需设置其它参数,必须设置其默认值,否则将**无法通过**自动评测,**成绩为零**。 +- 自动评测脚本仅会加载 `train_logreg`、`predict_logreg` 和 `load_data` 函数,请勿修改函数名。 +- 本地调试完成后,**需要更新提交代码**,否则无法自动评测,**没有实验成绩**。 +- 评测的运行时间受机器性能影响,运行时间仅供参考。 +- 若有评测相关问题,请在[项目工单](https://git.intcplab.cn/LufsX/Evaluation-Backend/issues)处提出,或联系 QQ: `1968647927`。 + +代码提交后会进行自动评测,评测所用的环境如下: + +- CPU: Intel Xeon(R) CPU E3-1231 v3 @ 3.40GHz +- OS: Ubuntu 22.04.4 LTS +- Python: 3.10.12 +- numpy: 2.1.1 + +## 实验操作 + +本次实验自带数据集,数据集在对应的 `data` 文件夹下。 + +本次实验强烈建议将代码克隆/下载到本地进行实验调试。 + +--- + +注意 ⚠️ + +若要完成实验,请确保是在**本页面**点击「使用模版」来创建仓库,新仓库名称建议与本模版名称 `Experiment-LogReg` 相同,其余操作参见[挑战赛的说明](https://git.intcplab.cn/LufsX/Challenge-kNN#挑战操作)。 + +若要完成实验,评测时检查创建完成的**仓库信息**是否正确,本次实验标题为「**实验二:对率回归与预测病马死亡**」! + +## 其它 + +若有流程、优化等相关建议和问题,欢迎在[评测后端项目工单](https://git.intcplab.cn/LufsX/Evaluation-Backend/issues)中提出。 + +同时欢迎参与[评测后端](https://git.intcplab.cn/LufsX/Evaluation-Backend)的开发与优化! diff --git a/data/Index b/data/Index new file mode 100755 index 0000000..6088203 --- /dev/null +++ b/data/Index @@ -0,0 +1,7 @@ +Index of horse-colic + +02 Dec 1996 212 Index +19 Jul 1992 9045 horse-colic.names +17 Jul 1992 25437 horse-colic.data +17 Jul 1992 9599 horse-colic.names.original +17 Jul 1992 5807 horse-colic.test diff --git a/data/horse-colic.data b/data/horse-colic.data new file mode 100755 index 0000000..9b49beb --- /dev/null +++ b/data/horse-colic.data @@ -0,0 +1,300 @@ +2 1 530101 38.50 66 28 3 3 ? 2 5 4 4 ? ? ? 3 5 45.00 8.40 ? ? 2 2 11300 00000 00000 2 +1 1 534817 39.2 88 20 ? ? 4 1 3 4 2 ? ? ? 4 2 50 85 2 2 3 2 02208 00000 00000 2 +2 1 530334 38.30 40 24 1 1 3 1 3 3 1 ? ? ? 1 1 33.00 6.70 ? ? 1 2 00000 00000 00000 1 +1 9 5290409 39.10 164 84 4 1 6 2 2 4 4 1 2 5.00 3 ? 48.00 7.20 3 5.30 2 1 02208 00000 00000 1 +2 1 530255 37.30 104 35 ? ? 6 2 ? ? ? ? ? ? ? ? 74.00 7.40 ? ? 2 2 04300 00000 00000 2 +2 1 528355 ? ? ? 2 1 3 1 2 3 2 2 1 ? 3 3 ? ? ? ? 1 2 00000 00000 00000 2 +1 1 526802 37.90 48 16 1 1 1 1 3 3 3 1 1 ? 3 5 37.00 7.00 ? ? 1 1 03124 00000 00000 2 +1 1 529607 ? 60 ? 3 ? ? 1 ? 4 2 2 1 ? 3 4 44.00 8.30 ? ? 2 1 02208 00000 00000 2 +2 1 530051 ? 80 36 3 4 3 1 4 4 4 2 1 ? 3 5 38.00 6.20 ? ? 3 1 03205 00000 00000 2 +2 9 5299629 38.30 90 ? 1 ? 1 1 5 3 1 2 1 ? 3 ? 40.00 6.20 1 2.20 1 2 00000 00000 00000 1 +1 1 528548 38.10 66 12 3 3 5 1 3 3 1 2 1 3.00 2 5 44.00 6.00 2 3.60 1 1 02124 00000 00000 1 +2 1 527927 39.10 72 52 2 ? 2 1 2 1 2 1 1 ? 4 4 50.00 7.80 ? ? 1 1 02111 00000 00000 2 +1 1 528031 37.20 42 12 2 1 1 1 3 3 3 3 1 ? 4 5 ? 7.00 ? ? 1 2 04124 00000 00000 2 +2 9 5291329 38.00 92 28 1 1 2 1 1 3 2 3 ? 7.20 1 1 37.00 6.10 1 ? 2 2 00000 00000 00000 1 +1 1 534917 38.2 76 28 3 1 1 1 3 4 1 2 2 ? 4 4 46 81 1 2 1 1 02112 00000 00000 2 +1 1 530233 37.60 96 48 3 1 4 1 5 3 3 2 3 4.50 4 ? 45.00 6.80 ? ? 2 1 03207 00000 00000 2 +1 9 5301219 ? 128 36 3 3 4 2 4 4 3 3 ? ? 4 5 53.00 7.80 3 4.70 2 2 01400 00000 00000 1 +2 1 526639 37.50 48 24 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? 1 2 00000 00000 00000 2 +1 1 5290481 37.60 64 21 1 1 2 1 2 3 1 1 1 ? 2 5 40.00 7.00 1 ? 1 1 04205 00000 00000 1 +2 1 532110 39.4 110 35 4 3 6 ? ? 3 3 ? ? ? ? ? 55 8.7 ? ? 1 2 00000 00000 00000 2 +1 1 530157 39.90 72 60 1 1 5 2 5 4 4 3 1 ? 4 4 46.00 6.10 2 ? 1 1 02111 00000 00000 2 +2 1 529340 38.40 48 16 1 ? 1 1 1 3 1 2 3 5.50 4 3 49.00 6.80 ? ? 1 2 00000 00000 00000 2 +1 1 521681 38.60 42 34 2 1 4 ? 2 3 1 ? ? ? 1 ? 48.00 7.20 ? ? 1 1 03111 00000 00000 2 +1 9 534998 38.3 130 60 ? 3 ? 1 2 4 ? ? ? ? ? ? 50 70 ? ? 1 1 03111 00000 00000 2 +1 1 533692 38.1 60 12 3 3 3 1 ? 4 3 3 2 2 ? ? 51 65 ? ? 1 1 03111 00000 00000 2 +2 1 529518 37.80 60 42 ? ? ? 1 ? ? ? ? ? ? ? ? ? ? ? ? 1 2 00000 00000 00000 2 +1 1 530526 38.30 72 30 4 3 3 2 3 3 3 2 1 ? 3 5 43.00 7.00 2 3.90 1 1 03111 00000 00000 1 +1 1 528653 37.80 48 12 3 1 1 1 ? 3 2 1 1 ? 1 3 37.00 5.50 2 1.30 1 2 04122 00000 00000 1 +1 1 5279442 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? 2 2 04300 00000 00000 2 +2 1 535415 37.7 48 ? 2 1 1 1 1 1 1 1 1 ? ? ? 45 76 ? ? 1 2 00000 00000 00000 2 +2 1 529475 37.70 96 30 3 3 4 2 5 4 4 3 2 4.00 4 5 66.00 7.50 ? ? 2 1 04205 00000 00000 2 +2 1 530242 37.20 108 12 3 3 4 2 2 4 2 ? 3 6.00 3 3 52.00 8.20 3 7.40 3 1 02207 00000 00000 1 +1 1 529427 37.20 60 ? 2 1 1 1 3 3 3 2 1 ? 4 5 43.00 6.60 ? ? 1 1 02209 00000 00000 2 +1 1 529663 38.20 64 28 1 1 1 1 3 1 ? ? ? ? 4 4 49.00 8.60 2 6.60 1 1 02208 00000 00000 1 +1 1 529796 ? 100 30 3 3 4 2 5 4 4 3 3 ? 4 4 52.00 6.60 ? ? 1 1 01124 00000 00000 2 +2 1 528812 ? 104 24 4 3 3 2 4 4 3 ? 3 ? ? 2 73.00 8.40 ? ? 3 1 07111 00000 00000 2 +2 1 529493 38.30 112 16 ? 3 5 2 ? ? 1 1 2 ? ? 5 51.00 6.00 2 1.00 3 2 05205 00000 00000 1 +1 1 533847 37.8 72 ? ? 3 ? 1 5 3 1 ? 1 ? 1 1 56 80 1 2 1 1 03111 00000 00000 2 +2 1 528996 38.60 52 ? 1 1 1 1 3 3 2 1 1 ? 1 3 32.00 6.60 1 5.00 1 2 00000 00000 00000 1 +1 9 5277409 39.20 146 96 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? 2 1 02113 00000 00000 2 +1 1 529498 ? 88 ? 3 3 6 2 5 3 3 1 3 ? 4 5 63.00 6.50 3 ? 2 1 04205 00000 00000 2 +2 9 5288249 39.00 150 72 ? ? ? ? ? ? ? ? ? ? ? ? 47.00 8.50 ? 0.10 1 1 09400 00000 00000 1 +2 1 530301 38.00 60 12 3 1 3 1 3 3 1 1 1 ? 2 2 47.00 7.00 ? ? 1 2 03111 00000 00000 2 +1 1 534069 ? 120 ? 3 4 4 1 4 4 4 1 1 ? ? 5 52 67 2 2 3 1 03205 00000 00000 2 +1 1 535407 35.4 140 24 3 3 4 2 4 4 ? 2 1 ? ? 5 57 69 3 2 3 1 03205 00000 00000 2 +2 1 529827 ? 120 ? 4 3 4 2 5 4 4 1 1 ? 4 5 60.00 6.50 3 ? 2 1 03205 00000 00000 2 +1 1 529888 37.90 60 15 3 ? 4 2 5 4 4 2 2 ? 4 5 65.00 7.50 ? ? 1 1 02305 00000 00000 1 +2 1 529821 37.50 48 16 1 1 1 1 1 1 1 1 1 ? 1 ? 37.00 6.50 ? ? 1 2 00000 00000 00000 2 +1 1 528890 38.90 80 44 3 3 3 2 2 3 3 2 2 7.00 3 1 54.00 6.50 3 ? 2 1 07111 00000 00000 2 +2 1 529642 37.20 84 48 3 3 5 2 4 1 2 1 2 ? 2 1 73.00 5.50 2 4.10 2 2 04300 00000 00000 1 +2 1 529766 38.60 46 ? 1 1 2 1 1 3 2 1 1 ? ? 2 49.00 9.10 1 1.60 1 2 03111 00000 00000 1 +1 1 527706 37.40 84 36 1 ? 3 2 3 3 2 ? ? ? 4 5 ? ? 3 ? 2 1 07209 00000 00000 1 +2 1 529483 ? ? ? 1 1 3 1 1 3 1 ? ? ? 2 2 43.00 7.70 ? ? 1 2 03111 00000 00000 2 +2 1 530544 38.60 40 20 ? ? ? 1 ? ? ? ? ? ? ? ? 41.00 6.40 ? ? 1 2 03111 00000 00000 1 +2 1 529461 40.30 114 36 3 3 1 2 2 3 3 2 1 7.00 1 5 57.00 8.10 3 4.50 3 1 07400 00000 00000 1 +1 9 5282839 38.60 160 20 3 ? 5 1 3 3 4 3 ? ? 4 ? 38.00 ? 2 ? 2 1 07111 00000 00000 1 +1 1 528872 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? 24.00 6.70 ? ? 1 1 03112 00000 00000 2 +1 1 529640 ? 64 36 2 ? 2 1 5 3 3 2 2 ? ? ? 42.00 7.70 ? ? 2 1 03209 00000 00000 2 +1 1 528298 ? ? 20 4 3 3 ? 5 4 3 2 ? ? 4 4 53.00 5.90 3 ? 2 1 03205 00000 00000 1 +2 1 528904 ? 96 ? 3 3 3 2 5 4 4 1 2 ? 4 5 60.00 ? ? ? 2 1 04205 00000 00000 2 +2 1 530438 37.80 48 32 1 1 3 1 2 1 ? 1 1 ? 4 5 37.00 6.70 ? ? 1 2 02124 00000 00000 2 +2 1 527957 38.50 60 ? 2 2 1 1 1 2 2 2 1 ? 1 1 44.00 7.70 ? ? 1 2 00000 00000 00000 2 +1 1 528630 37.80 88 22 2 1 2 1 3 ? ? 2 ? ? 4 ? 64.00 8.00 1 6.00 2 1 03205 00000 00000 1 +2 1 534293 38.2 130 16 4 3 4 2 2 4 4 1 1 ? ? ? 65 82 2 2 3 2 02209 01400 00000 2 +1 1 529667 39.00 64 36 3 1 4 2 3 3 2 1 2 7.00 4 5 44.00 7.50 3 5.00 1 1 02113 00000 00000 1 +1 1 534885 ? 60 36 3 1 3 1 3 3 2 1 1 ? 3 4 26 72 2 1 1 1 02208 00000 00000 2 +2 1 534784 37.9 72 ? 1 1 5 2 3 3 1 1 3 2 3 4 58 74 1 2 1 1 02322 00000 00000 2 +2 1 528931 38.40 54 24 1 1 1 1 1 3 1 2 1 ? 3 2 49.00 7.20 1 ? 1 2 03111 00000 00000 1 +2 1 529777 ? 52 16 1 ? 3 1 ? ? ? 2 3 5.50 ? ? 55.00 7.20 ? ? 1 2 02124 00000 00000 2 +2 1 530276 38.00 48 12 1 1 1 1 1 3 ? 1 1 ? 3 2 42.00 6.30 2 4.10 1 2 03111 00000 00000 1 +2 1 528214 37.00 60 20 3 ? ? 1 3 ? 3 2 2 4.50 4 4 43.00 7.60 ? ? 3 1 02209 00000 00000 1 +1 1 529424 37.80 48 28 1 1 1 1 1 2 1 2 ? ? 1 1 46.00 5.90 2 7.00 1 2 00000 00000 00000 1 +1 1 5299253 37.70 56 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? 2 1 02113 00000 00000 2 +1 1 528469 38.10 52 24 1 1 5 1 4 3 1 2 3 7.00 1 ? 54.00 7.50 2 2.60 2 1 02112 00000 00000 1 +1 9 5292929 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? 37.00 4.90 ? ? 2 1 11124 00000 00000 2 +1 9 534092 39.7 100 ? 3 3 5 2 2 3 ? ? ? ? ? ? 48 57 2 2 3 1 01400 00000 00000 2 +1 1 534615 37.6 38 20 3 3 1 1 3 3 2 ? ? ? 3 ? 37 68 ? ? 1 1 03205 00000 00000 2 +2 1 534753 38.7 52 20 2 ? 1 1 1 1 1 1 1 ? 1 1 33 77 ? ? 1 2 00000 00000 00000 2 +1 1 530693 ? ? ? 3 3 3 3 5 3 3 3 2 ? 4 5 46.00 5.90 ? ? 2 1 03025 00000 00000 2 +1 1 527463 37.50 96 18 1 3 6 2 3 4 2 2 3 5.00 ? 4 69.00 8.90 3 ? 1 1 02208 00000 00000 1 +1 1 527518 36.40 98 35 3 3 4 1 4 3 2 ? ? ? 4 4 47.00 6.40 3 3.60 2 1 02205 00000 00000 1 +1 1 534756 37.3 40 ? ? 3 1 1 2 3 2 3 1 ? 3 5 36 ? 3 2 1 1 03111 00000 00000 2 +1 9 5290759 38.10 100 80 3 1 2 1 3 4 1 ? ? ? 1 ? 36.00 5.70 ? ? 1 1 03111 00000 00000 2 +1 1 5279822 38.00 ? 24 3 3 6 2 5 ? 4 1 1 ? ? ? 68.00 7.80 ? ? 2 1 03205 00000 00000 2 +1 1 529849 37.80 60 80 1 3 2 2 2 3 3 ? 2 5.50 4 ? 40.00 4.50 2 ? 1 1 05206 00000 00000 1 +2 1 529304 38.00 54 30 2 3 3 3 3 1 2 2 2 ? ? 4 45.00 6.20 ? ? 1 2 00400 00000 00000 2 +1 1 529388 ? 88 40 3 3 4 2 5 4 3 3 ? ? 4 5 50.00 7.70 3 1.40 2 1 04205 00000 00000 1 +2 1 528006 ? 40 16 ? ? ? 1 ? ? ? ? ? ? ? ? 50.00 7.00 2 3.90 3 1 02208 00000 00000 1 +2 1 529703 39.00 64 40 1 1 5 1 3 3 2 2 1 ? 3 3 42.00 7.50 2 2.30 1 2 05000 00000 00000 1 +2 1 535381 38.3 42 10 1 1 1 1 1 1 1 ? ? ? ? ? 38 61 ? ? 1 2 00000 00000 00000 2 +2 1 534197 38.0 52 16 ? ? ? ? 2 ? ? ? 3 1 1 1 53 86 ? ? 1 1 02322 00000 00000 2 +2 1 529461 40.30 114 36 3 3 1 2 2 3 3 2 1 7.00 1 5 57.00 8.10 3 4.50 2 1 03205 00000 00000 1 +2 1 530251 38.80 50 20 3 1 1 1 1 1 1 2 1 ? 3 1 42.00 6.20 ? ? 1 2 00000 00000 00000 2 +2 1 530310 ? ? ? 3 3 1 1 5 3 3 1 1 ? 4 5 38.00 6.50 ? ? 2 1 03205 00000 00000 2 +2 1 528729 37.50 48 30 4 1 3 1 ? 2 1 1 1 ? 1 1 48.00 8.60 ? ? 1 2 00000 00000 00000 2 +1 1 535158 37.3 48 20 ? 1 2 1 3 3 3 2 1 ? 3 5 41 69 ? ? 1 1 03205 00000 00000 2 +2 1 530319 ? 84 36 ? ? 3 1 ? 3 1 2 1 ? 3 2 44.00 8.50 ? ? 1 1 03111 00000 00000 2 +1 1 534145 38.1 88 32 3 3 4 1 2 3 3 ? 3 1 4 5 55 60 ? ? 3 2 03205 00000 00000 2 +2 1 534135 37.7 44 40 2 1 3 1 1 3 2 1 1 ? 1 5 41 60 ? ? 1 2 00000 00000 00000 2 +2 1 530002 39.60 108 51 3 3 6 2 2 4 3 1 2 ? 3 5 59.00 8.00 2 2.60 1 2 04300 00000 00000 1 +1 1 535364 38.2 40 16 3 3 1 1 1 3 ? ? ? ? 1 1 34 66 ? ? 1 2 00000 00000 00000 2 +1 1 534899 ? 60 20 4 3 4 2 5 4 ? ? 1 ? 4 5 ? ? ? ? 3 1 03205 00000 00000 2 +2 1 534938 38.3 40 16 3 ? 1 1 2 ? ? ? ? ? ? ? 37 57 ? ? 1 2 00000 00000 00000 2 +1 9 5292489 38.00 140 68 1 1 1 1 3 3 2 ? ? ? 2 1 39.00 5.30 ? ? 1 1 07111 00000 00000 2 +1 1 527563 37.80 52 24 1 3 3 1 4 4 1 2 3 5.70 2 5 48.00 6.60 1 3.70 2 1 05400 00000 00000 2 +1 1 530381 ? 70 36 1 ? 3 2 2 3 2 2 ? ? 4 5 36.00 7.30 ? ? 1 1 31110 00000 00000 2 +1 1 528668 38.30 52 96 ? 3 3 1 ? ? ? 1 1 ? 1 ? 43.00 6.10 ? ? 1 1 03209 00000 00000 1 +2 1 529764 37.30 50 32 1 1 3 1 1 3 2 ? ? ? 1 ? 44.00 7.00 ? ? 1 2 00000 00000 00000 2 +1 1 533696 38.7 60 32 4 3 2 2 4 4 4 ? ? ? 4 5 53 64 3 2 3 1 03205 00000 00000 2 +1 9 5297379 38.40 84 40 3 3 2 1 3 3 3 1 1 ? ? ? 36.00 6.60 2 2.80 2 1 02205 00000 00000 1 +1 1 527544 ? 70 16 3 4 5 2 2 3 2 2 1 ? 4 5 60.00 7.50 ? ? 2 1 02112 00000 00000 2 +1 1 533736 38.3 40 16 3 ? ? 1 1 3 2 ? ? ? ? ? 38 58 1 2 1 1 03111 07111 00000 2 +1 1 534963 ? 40 ? 2 1 1 1 1 3 1 1 1 ? ? 5 39 56 ? ? 1 1 03111 00000 00000 2 +1 1 527933 36.80 60 28 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? 10.00 2 1 03205 00000 00000 1 +1 1 532349 38.4 44 24 3 ? 4 ? 5 4 3 2 1 ? 4 5 50 77 ? ? 1 1 03205 00000 00000 2 +2 1 533723 ? ? 40 3 1 1 1 3 3 2 ? ? ? ? ? 45 70 ? ? 1 2 00000 00000 00000 2 +1 1 535208 38.0 44 12 1 1 1 1 3 3 3 2 1 ? 4 5 42 65 ? ? 1 1 03205 03111 00000 2 +2 1 5290482 39.50 ? ? 3 3 4 2 3 4 3 ? 3 5.50 4 5 ? 6.70 1 ? 3 1 04205 00000 00000 2 +1 1 533983 36.5 78 30 1 ? 1 1 5 3 1 ? 1 ? ? ? 34 75 2 1 1 1 03112 06112 00000 2 +2 1 535166 38.1 56 20 2 1 2 1 1 3 1 1 1 ? ? ? 46 70 ? ? 1 2 00000 00000 00000 2 +1 1 528682 39.40 54 66 1 1 2 1 2 3 2 1 1 ? 3 4 39.00 6.00 2 ? 1 1 02206 00000 00000 1 +1 1 534556 38.3 80 40 ? ? 6 2 4 3 1 ? 2 ? 1 4 67 10.2 2 1 3 1 02208 00000 00000 2 +2 1 534579 38.7 40 28 2 1 1 1 3 1 1 ? ? ? 1 ? 39 62 1 1 1 2 00000 00000 00000 2 +1 1 530360 38.20 64 24 1 1 3 1 4 4 3 2 1 ? 4 4 45.00 7.50 1 2.00 2 1 03205 00000 00000 1 +2 1 529840 37.60 48 20 3 1 4 1 1 1 3 2 1 ? 1 1 37.00 5.50 ? ? 3 1 02205 00000 00000 2 +1 1 528461 38.00 42 68 4 1 1 1 3 3 2 2 2 ? 4 4 41.00 7.60 ? ? 1 1 02205 00000 00000 2 +1 1 530384 38.70 ? ? 3 1 3 1 5 4 2 ? ? ? ? ? 33.00 6.50 2 ? 1 1 31110 00000 00000 2 +1 1 5262541 37.40 50 32 3 3 ? 1 4 4 1 2 1 ? 1 ? 45.00 7.90 2 1.00 1 1 02208 00000 00000 1 +1 1 535330 37.4 84 20 ? ? 3 1 2 3 3 ? ? ? ? ? 31 61 ? 1 3 2 02208 00000 00000 2 +1 1 527698 38.40 49 ? ? ? 1 1 ? ? 1 2 1 ? ? ? 44.00 7.60 ? ? 1 1 02206 00000 00000 2 +1 1 528964 37.80 30 12 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? 2 1 02113 00000 00000 2 +2 1 530670 37.60 88 36 3 1 1 1 3 3 2 1 3 1.50 ? ? 44.00 6.00 ? ? 2 1 01400 00000 00000 2 +? 1 534572 38.0 48 20 3 1 3 1 4 3 1 2 1 ? 3 5 43 73 2 1 ? 1 03111 00000 00000 2 +2 1 530294 37.90 40 24 1 1 1 1 2 3 1 ? ? ? ? 3 40.00 5.70 ? ? 1 1 00400 00000 00000 2 +1 1 527524 ? 100 ? 3 ? 4 2 5 4 ? 2 ? ? 2 ? 59.00 6.30 ? ? 2 1 04205 00000 00000 2 +1 9 5287179 38.10 136 48 3 3 3 1 5 1 3 2 2 4.40 2 ? 33.00 4.90 2 2.90 2 1 02205 00000 00000 1 +1 1 530693 ? ? ? 3 3 3 2 5 3 3 3 2 ? 4 5 46.00 5.90 ? ? 2 1 03025 00000 00000 2 +1 1 534324 38 48 ? 1 1 1 1 1 2 4 2 2 ? 4 5 ? ? ? ? 1 1 03111 00000 00000 2 +2 1 532349 38 56 ? 1 2 3 1 1 1 1 1 1 ? 1 1 42 71 ? ? 1 2 00000 00000 00000 2 +2 1 534491 38 60 32 1 1 ? 1 3 3 ? 1 1 ? ? ? 50 7.0 1 1 1 2 00000 00000 00000 2 +1 1 529960 38.10 44 9 3 1 1 1 2 2 1 1 1 ? 4 5 31.00 7.30 ? ? 1 2 05124 00000 00000 2 +2 1 522979 36.00 42 30 ? ? 5 1 ? ? ? ? ? ? ? ? 64.00 6.80 ? ? 2 2 01400 00000 00000 2 +1 1 530402 ? 120 ? 4 3 6 2 5 4 4 ? ? ? 4 5 57.00 4.50 3 3.90 2 1 03205 00000 00000 1 +1 1 529424 37.80 48 28 1 1 1 2 1 2 1 2 ? ? 1 1 46.00 5.90 2 7.00 1 2 00000 00000 00000 1 +1 1 534519 37.1 84 40 3 3 6 1 2 4 4 3 2 2 4 5 75 81 ? ? 3 2 01400 00000 00000 2 +2 1 535246 ? 80 32 3 3 2 1 2 3 3 2 1 ? 3 ? 50 80 ? ? 1 1 00000 00000 00000 2 +1 1 534115 38.2 48 ? 1 3 3 1 3 4 4 1 3 2 4 5 42 71 ? ? 1 1 03111 00000 00000 2 +2 1 530001 38.00 44 12 2 1 3 1 3 4 3 1 2 6.50 1 4 33.00 6.50 ? ? 2 1 02209 00000 00000 2 +1 1 529272 38.30 132 ? ? 3 6 2 2 4 2 2 3 6.20 4 4 57.00 8.00 ? 5.20 1 1 02112 00000 00000 1 +2 1 535314 38.7 48 24 ? ? ? ? 1 1 ? 1 1 ? 1 ? 34 63 ? ? 1 2 00000 00000 00000 2 +2 1 533793 38.9 44 14 3 1 1 1 2 3 2 ? ? ? ? 2 33 64 ? ? 1 2 00000 00000 00000 2 +1 1 529399 39.30 ? ? 4 3 6 2 4 4 2 1 3 4.00 4 4 75.00 ? 3 4.30 2 1 02207 00000 00000 1 +1 1 533836 ? 100 ? 3 3 4 2 ? 4 4 2 1 2 ? ? 68 64 3 2 1 1 02209 00000 00000 2 +2 1 528804 38.60 48 20 3 1 1 1 1 3 2 2 1 ? 3 2 50.00 7.30 1 ? 1 2 03111 00000 00000 1 +2 1 535163 38.8 48 40 1 1 3 1 3 3 4 2 ? ? ? 5 41 65 ? ? 1 1 04124 00000 000000 2 +2 1 528247 38.00 48 20 3 3 4 1 1 4 2 2 ? 5.00 ? 2 49.00 8.30 1 ? 1 2 00400 00000 00000 1 +2 1 528996 38.60 52 20 1 1 1 1 3 3 2 1 1 ? 1 3 36.00 6.60 1 5.00 1 2 00000 00000 00000 1 +1 1 533928 37.8 60 24 1 ? 3 2 ? 4 4 2 3 2 ? 5 52 75 ? ? 3 1 02205 00000 00000 2 +2 1 528248 38.00 42 40 3 1 1 1 3 3 1 ? ? ? ? ? ? ? ? ? 1 2 03111 00000 00000 2 +2 1 528134 ? ? 12 1 1 2 1 2 1 2 3 1 ? 1 3 44.00 7.50 2 ? 1 2 00000 00000 00000 1 +1 1 527916 ? ? ? ? ? ? ? 4 ? ? 1 1 ? ? 5 35 58 2 1 1 1 04205 00000 00000 2 +1 1 530431 38.30 42 24 ? ? ? 1 ? ? ? ? ? ? ? ? 40.00 8.50 ? ? 2 1 07113 00000 00000 2 +2 1 535176 39.5 60 10 3 ? ? 2 3 3 2 2 1 ? 3 ? 38 56 1 ? 1 2 00000 00000 00000 2 +1 1 533942 38 66 20 1 3 3 1 5 3 1 1 1 ? 3 ? 46 46 3 2 3 1 06209 00000 00000 2 +1 1 528523 38.70 76 ? 1 1 5 2 3 3 2 2 2 ? 4 4 50.00 8.00 ? ? 1 1 02208 00000 00000 1 +1 1 534925 39.4 120 48 ? ? 5 1 ? 3 3 1 ? ? 4 ? 56 64 1 2 3 2 01400 00000 00000 2 +1 1 527916 38.30 40 18 1 1 1 1 3 1 1 ? ? ? 2 1 43.00 5.90 1 ? 1 2 00000 00000 00000 1 +2 1 528299 ? 44 24 1 1 1 1 3 3 1 2 1 ? ? 1 ? 6.30 ? ? 1 2 03111 00000 00000 2 +1 1 530254 38.40 104 40 1 1 3 1 2 4 2 2 3 6.50 ? 4 55.00 8.50 ? ? 1 1 02124 00000 00000 2 +1 1 535085 ? 65 24 ? ? ? 2 5 ? 4 3 1 ? ? 5 ? ? ? ? 3 1 03205 00000 00000 2 +2 1 532985 37.5 44 20 1 1 3 1 ? 1 1 ? ? ? 1 ? 35 7.2 ? ? 1 2 00000 00000 00000 2 +2 1 527677 39.00 86 16 3 3 5 ? 3 3 3 ? 2 ? ? ? 68.00 5.80 3 6.00 2 1 05400 00000 00000 1 +1 1 535292 38.5 129 48 3 3 3 1 2 4 3 1 3 2 ? ? 57 66 3 2 1 1 02206 00000 00000 2 +1 1 529729 ? 104 ? 3 3 5 2 2 4 3 ? 3 ? 4 4 69.00 8.60 2 3.40 2 1 02207 00000 00000 1 +2 1 518476 ? ? ? 3 4 6 ? 4 ? 4 ? ? ? ? ? ? ? ? ? 2 1 03400 00000 00000 1 +1 1 527929 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? 1 1 02208 00000 00000 2 +1 1 535130 38.2 60 30 1 1 3 1 3 3 1 2 1 ? 3 2 48 66 ? ? 1 1 06112 00000 00000 2 +1 1 523190 ? 68 14 ? ? 4 1 4 ? ? ? 1 4.30 ? ? ? ? 2 2.80 2 1 04205 00000 00000 1 +1 1 533968 ? 60 30 3 3 4 2 5 4 4 1 1 ? 4 ? 45 70 3 2 1 1 06111 03111 00000 2 +2 1 528151 38.50 100 ? 3 3 5 2 4 3 4 2 1 ? 4 5 ? ? ? ? 3 2 01111 00000 00000 1 +1 1 530239 38.40 84 30 3 1 5 2 4 3 3 2 3 6.50 4 4 47.00 7.50 3 ? 2 1 02300 00000 00000 2 +2 1 528305 37.80 48 14 ? ? 1 1 3 ? 2 1 3 5.30 1 ? 35.00 7.50 ? ? 1 2 03111 00000 00000 1 +1 1 5279822 38.00 ? 24 3 3 6 2 5 ? 4 1 1 ? ? ? 68.00 7.80 ? ? 2 1 02205 00000 00000 2 +2 1 534857 37.8 56 16 1 1 2 1 2 1 1 2 1 ? 1 ? 44 68 1 1 1 2 00000 00000 00000 2 +2 1 534053 38.2 68 32 2 2 2 1 1 1 1 3 1 ? 1 1 43 65 ? ? 1 2 00000 00000 00000 2 +1 1 534833 38.5 120 60 4 3 6 2 ? 3 ? ? ? ? ? ? 54 ? ? ? 1 1 05400 00000 00000 2 +1 1 5278331 39.30 64 90 2 3 1 1 ? 3 1 1 2 ? ? ? 39.00 6.70 ? ? 1 1 21110 00000 00000 2 +1 1 527365 38.40 80 30 4 3 1 1 3 3 3 3 3 ? 4 5 32.00 6.10 3 4.30 1 1 07209 00000 00000 1 +1 1 533887 38.5 60 ? 1 1 ? 1 ? 1 1 ? ? ? ? ? 33 53 1 ? 1 1 04111 00000 00000 2 +1 1 5299603 38.30 60 16 3 1 1 1 2 1 1 2 2 3.00 1 4 30.00 6.00 1 3.00 1 1 31110 00000 00000 2 +1 1 528742 37.10 40 8 ? 1 4 1 3 3 1 1 1 ? 3 3 23.00 6.70 3 ? 1 1 03133 00000 00000 1 +2 9 5287279 ? 100 44 2 1 1 1 4 1 1 ? ? ? 1 ? 37.00 4.70 ? ? 1 2 07111 00000 00000 2 +1 1 534788 38.2 48 18 1 1 1 1 3 3 3 1 2 ? 4 ? 48 74 1 2 1 1 05111 00000 00000 2 +1 1 529373 ? 60 48 3 3 4 2 4 3 4 ? ? ? ? ? 58.00 7.60 ? ? 2 1 03205 00000 00000 2 +2 1 534163 37.9 88 24 1 1 2 1 2 2 1 ? ? ? 4 1 37 56 ? ? 1 2 00000 00000 00000 2 +2 1 533697 38.0 44 12 3 1 1 ? ? 1 2 ? ? ? 1 ? 42 64 ? ? 1 2 00000 00000 00000 2 +2 1 529628 38.50 60 20 1 1 5 2 2 2 1 2 1 ? 2 3 63.00 7.50 2 2.30 3 2 00300 00000 00000 1 +2 1 521399 38.50 96 36 3 3 ? 2 2 4 2 1 2 ? 4 5 70.00 8.50 ? ? 2 1 01400 00000 00000 1 +2 1 533885 38.3 60 20 1 1 1 2 1 3 1 ? ? ? 3 ? 34 66 ? ? 1 2 00000 00000 00000 2 +2 1 534157 38.5 60 40 3 1 2 1 2 1 2 ? ? ? 3 2 49 59 ? ? 1 2 00000 00000 00000 2 +1 1 528047 37.30 48 12 1 ? 3 1 3 1 3 2 1 ? 3 3 40.00 6.60 2 ? 1 1 03205 00000 00000 1 +1 1 528641 38.50 86 ? 1 1 3 1 4 4 3 2 1 ? 3 5 45.00 7.40 1 3.40 2 1 03209 00000 00000 1 +1 1 534073 37.5 48 40 ? ? ? ? ? ? ? 1 1 ? ? 5 41 55 3 2 3 1 02208 00000 00000 2 +2 1 529685 37.20 36 9 1 1 1 1 2 3 1 2 1 ? 4 1 35.00 5.70 ? ? 1 2 31110 00000 00000 2 +1 1 529528 39.20 ? 23 3 1 3 1 4 4 2 2 ? ? ? ? 36.00 6.60 1 3.00 1 1 03115 00000 00000 1 +2 1 528151 38.50 100 ? 3 3 5 2 4 3 4 2 1 ? 4 5 ? ? ? ? 3 2 04124 00000 00000 2 +1 1 535137 38.5 96 30 2 3 4 2 4 4 3 2 1 ? 3 5 50 65 ? ? 1 1 06111 03112 00000 2 +1 1 530297 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? 45.00 8.70 ? ? 2 1 02208 00000 00000 2 +1 1 535338 37.8 88 80 3 3 5 2 ? 3 3 2 3 ? 4 5 64 89 ? ? 3 1 03205 00000 00000 2 +2 1 534478 37.5 44 10 3 1 1 1 3 1 2 2 ? ? 3 3 43 51 1 1 1 2 00000 00000 00000 2 +1 1 530401 37.90 68 20 ? 1 2 1 2 4 2 ? ? ? 1 5 45.00 4.00 3 2.80 2 1 05400 00000 00000 1 +1 1 529893 38.00 86 24 4 3 4 1 2 4 4 1 1 ? 4 5 45.00 5.50 1 10.10 2 1 03111 00000 00000 1 +1 9 5294369 38.90 120 30 1 3 2 2 3 3 3 3 1 3.00 ? ? 47.00 6.30 1 ? 1 2 02124 00000 00000 2 +1 1 528183 37.60 45 12 3 1 3 1 ? 2 2 2 1 ? 1 4 39.00 7.00 2 1.50 1 1 02112 00000 00000 1 +2 1 529183 38.60 56 32 2 1 1 1 1 1 1 2 ? ? 2 ? 40.00 7.00 2 2.10 1 2 00000 00000 00000 1 +1 1 529135 37.80 40 12 1 1 1 1 1 2 1 2 1 ? 1 2 38.00 7.00 ? ? 1 1 03111 00000 00000 2 +2 1 528977 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? 1 2 00000 00000 00000 2 +1 1 5279441 38.00 76 18 ? ? ? 2 ? ? ? ? ? ? ? ? 71.00 11.00 ? ? 1 1 02209 00000 00000 1 +1 1 535240 38.1 40 36 1 2 2 1 2 2 ? ? ? ? ? ? ? ? ? ? 3 1 03112 00000 00000 2 +1 1 529736 ? 52 28 3 3 4 1 3 4 3 2 1 ? 4 4 37.00 8.10 ? ? 1 1 02111 00000 00000 2 +1 1 535029 39.2 88 58 4 4 ? 2 5 4 ? ? ? ? ? ? ? ? 2 2 3 2 03205 00000 00000 2 +1 1 535031 38.5 92 40 4 3 ? 1 2 4 3 ? ? ? 4 ? 46 67 2 2 1 1 02208 00000 00000 2 +1 1 528800 ? 112 13 4 4 4 1 2 3 1 2 1 4.50 4 4 60.00 6.30 3 ? 1 1 02205 00000 00000 1 +1 1 528178 37.70 66 12 1 1 3 1 3 3 2 2 ? ? 4 4 31.50 6.20 2 1.60 1 1 02208 00000 00000 1 +1 1 535392 38.8 50 14 1 1 1 1 3 1 1 1 1 ? 3 5 38 58 ? ? 1 1 03111 00000 00000 2 +2 1 528931 38.40 54 24 1 1 1 1 1 3 1 2 1 ? 3 2 49.00 7.20 1 8.00 1 2 03111 00000 00000 1 +1 1 528503 39.20 120 20 4 3 5 2 2 3 3 1 3 ? ? 4 60.00 8.80 3 ? 2 1 02205 00000 00000 2 +1 9 5289419 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? 45.00 6.50 2 ? 1 1 09000 00000 00000 1 +1 1 535196 37.3 90 40 3 ? 6 2 5 4 3 2 2 ? 1 5 65 50 3 2 3 1 03205 00000 00000 2 +1 9 534597 38.5 120 70 ? ? ? ? ? 1 ? 2 ? ? 1 ? 35 54 1 1 1 1 04205 03111 02209 2 +1 1 534280 38.5 104 40 3 3 ? 1 4 3 4 ? ? ? ? ? ? ? ? ? 1 1 02124 00000 00000 2 +2 1 530028 39.50 92 28 3 3 6 1 5 4 1 ? 3 ? 4 ? 72.00 6.40 ? 3.60 2 2 03300 00000 00000 2 +1 1 5262543 38.50 30 18 ? ? ? ? ? ? ? ? ? ? ? ? 40.00 7.70 ? ? 1 1 02113 00000 00000 2 +1 1 530526 38.30 72 30 4 3 3 2 3 3 3 2 1 ? 3 5 43.00 7.00 2 3.90 1 1 03113 00000 00000 1 +2 1 528729 37.50 48 30 4 1 3 1 ? 2 1 1 1 ? 1 1 48.00 8.60 ? ? 1 2 00400 00000 00000 2 +1 1 528469 38.10 52 24 1 1 5 1 4 3 1 2 3 7.00 1 ? 54.00 7.50 2 2.60 2 1 02206 00000 00000 1 +2 1 528179 38.20 42 26 1 1 1 1 3 1 2 ? ? ? 1 ? 36.00 6.90 ? ? 1 2 03111 00000 00000 2 +2 1 533750 37.9 54 42 2 1 5 1 3 1 1 ? 1 ? ? 2 47 54 3 1 1 2 00000 00000 00000 2 +2 1 528702 36.10 88 ? 3 3 3 1 3 3 2 2 3 ? ? 4 45.00 7.00 3 4.80 3 1 02209 00000 00000 1 +1 1 534183 38.1 70 22 ? 1 ? 1 5 3 ? ? ? ? ? 5 36 65 ? ? 3 1 03205 00000 00000 2 +1 1 529160 38.00 90 30 4 3 4 2 5 4 4 ? ? ? 4 5 55.00 6.10 ? ? 2 1 03205 00000 00000 2 +1 1 529045 38.20 52 16 1 1 2 1 1 2 1 1 1 ? 1 ? 43.00 8.10 ? ? 1 2 00000 00000 00000 1 +1 1 530354 ? 36 32 1 1 4 1 5 3 3 2 3 4.00 ? 4 41.00 5.90 ? ? 2 1 02205 00000 00000 2 +1 1 5281091 38.40 92 20 1 ? ? 2 ? 3 3 ? ? ? 1 ? ? ? ? ? 1 1 02208 00000 00000 1 +1 9 5291409 38.20 124 88 1 3 2 1 2 3 4 ? ? ? ? ? 47.00 8.00 1 ? 1 1 09400 00000 00000 1 +2 1 528904 ? 96 ? 3 3 3 2 5 4 4 ? 1 ? 4 5 60.00 ? ? ? 2 1 41110 00000 00000 2 +1 1 530366 37.60 68 32 3 ? 3 1 4 2 4 2 2 6.50 1 5 47.00 7.20 1 ? 1 1 03209 00000 00000 2 +1 1 530170 38.10 88 24 3 3 4 1 5 4 3 2 1 ? 3 4 41.00 4.60 ? ? 2 1 02209 00000 00000 2 +1 1 527709 38.00 108 60 2 3 4 1 4 3 3 2 ? ? 3 4 ? ? 3 ? 1 1 02205 00000 00000 2 +2 1 528169 38.20 48 ? 2 ? 1 2 3 3 1 2 1 ? ? 2 34.00 6.60 ? ? 1 2 03111 00000 00000 2 +1 1 535043 39.3 100 51 4 4 6 1 2 4 1 1 3 2 ? 4 66 13 3 2 3 1 02113 00000 00000 2 +2 1 527940 36.60 42 18 3 3 2 1 1 4 1 1 1 ? ? 5 52.00 7.10 ? ? 2 1 05111 00000 00000 2 +1 9 5291719 38.80 124 36 3 1 2 1 2 3 4 1 1 ? 4 4 50.00 7.60 3 ? 2 1 02208 00000 00000 1 +2 1 530561 ? 112 24 3 3 4 2 5 4 2 ? ? ? 4 ? 40.00 5.30 3 2.60 1 2 00400 00000 00000 1 +1 1 533738 ? 80 ? 3 3 3 1 4 4 4 ? ? ? 4 5 43 70 ? ? 1 1 03111 00000 00000 2 +1 9 5294539 38.80 184 84 1 ? 1 1 4 1 3 ? ? ? 2 ? 33.00 3.30 ? ? 2 1 07111 00000 00000 2 +1 1 533871 37.5 72 ? 2 1 1 1 2 1 1 1 1 ? 1 ? 35 65 2 2 3 1 07209 00000 00000 2 +1 1 529812 38.70 96 28 3 3 4 1 ? 4 ? ? 3 7.50 ? ? 64.00 9.00 ? ? 2 1 02205 00000 00000 1 +2 1 534719 37.5 52 12 1 1 1 1 2 3 2 2 1 ? 3 5 36 61 1 1 1 2 00000 00000 00000 2 +1 1 527734 40.80 72 42 3 3 1 1 2 3 1 2 1 ? ? ? 54.00 7.40 3 ? 2 1 11400 00000 00000 1 +2 1 534933 38 40 25 ? 1 1 1 4 3 2 1 1 ? 4 ? 37 69 ? ? 1 2 00000 00000 00000 2 +2 1 529296 38.40 48 16 2 1 1 1 1 ? 2 2 1 ? ? 2 39.00 6.50 ? ? 1 2 03111 00000 00000 1 +2 9 5305629 38.60 88 28 ? ? ? ? ? ? ? ? ? ? ? ? 35.00 5.90 ? ? 1 2 00000 00000 00000 2 +1 1 528743 37.10 75 36 ? ? 3 2 4 4 2 2 3 5.00 4 4 48.00 7.40 3 3.20 2 1 12208 00000 00000 1 +1 1 530478 38.30 44 21 3 1 2 1 3 3 3 2 1 ? 1 5 44.00 6.50 2 4.40 1 1 02209 00000 00000 1 +2 1 528590 ? 56 68 3 1 1 1 3 3 1 2 1 ? 1 ? 40.00 6.00 ? ? 3 1 05206 00000 00000 2 +2 1 529865 38.60 68 20 2 1 3 1 3 3 2 1 1 ? 1 5 38.00 6.50 1 ? 1 2 05124 00000 00000 1 +2 1 527829 38.30 54 18 3 1 2 1 2 3 2 ? 3 5.40 ? 4 44.00 7.20 3 ? 1 2 02124 00000 00000 1 +1 1 534403 38.2 42 20 ? ? 1 1 ? 3 ? ? ? ? 3 ? 47 60 ? ? 1 2 00000 00000 00000 2 +1 1 527883 39.30 64 90 2 3 1 1 ? 3 1 1 2 6.50 1 5 39.00 6.70 ? ? 1 1 31110 00000 00000 2 +1 1 528570 37.50 60 50 3 3 1 1 3 3 2 2 2 3.50 3 4 35.00 6.50 ? ? 2 1 02209 00000 00000 2 +1 1 534626 37.7 80 ? 3 3 6 1 5 4 1 2 3 ? 3 1 50 55 3 2 1 1 04206 00000 00000 2 +1 1 529796 ? 100 30 3 3 4 2 5 4 4 3 3 ? 4 4 52.00 6.60 ? ? 1 1 02124 00000 00000 2 +1 1 528638 37.70 120 28 3 3 3 1 5 3 3 1 1 ? ? ? 65.00 7.00 3 ? 2 1 04205 00000 00000 1 +1 1 534624 ? 76 ? ? 3 ? ? ? 4 4 ? ? ? ? 5 ? ? ? ? 3 1 11124 00000 00000 2 +1 9 5297159 38.80 150 50 1 3 6 2 5 3 2 1 1 ? ? ? 50.00 6.20 ? ? 2 1 04207 00000 00000 2 +1 1 534787 38.0 36 16 3 1 1 1 4 2 2 3 3 2 3 ? 37 75 2 1 3 2 03111 00000 00000 2 +2 1 528620 36.90 50 40 2 3 3 1 1 3 2 3 1 7.00 ? ? 37.50 6.50 ? ? 1 2 03111 00000 00000 2 +2 1 528019 37.80 40 16 1 1 1 1 1 1 1 ? ? ? 1 1 37.00 6.80 ? ? 1 2 00000 00000 00000 2 +2 1 529172 38.20 56 40 4 3 1 1 2 4 3 2 2 7.50 ? ? 47.00 7.20 1 2.50 1 2 08300 00000 00000 1 +1 1 534644 38.6 48 12 ? ? 1 ? 1 1 ? ? ? ? ? ? 36 67 ? ? 1 2 00000 00000 00000 2 +2 1 530624 40.00 78 ? 3 3 5 1 2 3 1 1 1 ? 4 1 66.00 6.50 ? ? 2 1 08400 00000 00000 1 +1 1 527544 ? 70 16 3 4 5 2 2 3 2 2 1 ? 4 5 60.00 7.50 ? ? 2 1 01400 00000 00000 2 +1 1 527758 38.20 72 18 ? ? ? ? ? ? ? ? ? ? ? ? 35.00 6.40 ? ? 1 1 03124 00000 00000 2 +2 1 530439 38.50 54 ? 1 1 1 1 3 1 1 2 1 ? 1 ? 40.00 6.80 2 7.00 1 2 00000 00000 00000 1 +1 1 5283431 38.50 66 24 1 1 1 1 3 3 1 2 1 ? 4 5 40.00 6.70 1 ? 1 1 31110 00000 00000 1 +2 1 5275212 37.80 82 12 3 1 1 2 4 ? 3 1 3 ? ? ? 50.00 7.00 ? ? 3 1 02205 00000 00000 2 +2 9 5305129 39.50 84 30 ? ? ? 1 ? ? ? ? ? ? ? ? 28.00 5.00 ? ? 1 2 00000 00000 00000 2 +1 1 529428 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? 1 1 02124 00000 00000 2 +1 1 529126 38.00 50 36 ? 1 1 1 3 2 2 ? ? ? 3 ? 39.00 6.60 1 5.30 1 1 08400 00000 00000 1 +2 1 535054 38.6 45 16 2 1 2 1 1 1 ? ? ? ? 1 1 43 58 ? ? 1 2 00000 00000 00000 2 +1 1 528890 38.90 80 44 3 3 3 1 2 3 3 2 2 7.00 3 1 54.00 6.50 3 ? 2 1 07111 00000 00000 2 +1 1 530034 37.00 66 20 1 3 2 1 4 3 3 1 ? ? 1 5 35.00 6.90 2 ? 2 1 31110 00000 00000 2 +1 1 534004 ? 78 24 3 3 3 1 ? 3 ? 2 1 ? ? 4 43 62 ? 2 3 2 02209 00000 00000 2 +2 1 533902 38.5 40 16 1 1 1 1 2 1 1 ? ? ? 3 2 37 67 ? ? 1 2 00000 00000 00000 2 +1 1 533886 ? 120 70 4 ? 4 2 2 4 ? ? ? ? ? 5 55 65 ? ? 3 2 03205 00000 00000 2 +2 1 527702 37.20 72 24 3 2 4 2 4 3 3 3 1 ? 4 4 44.00 ? 3 3.30 3 1 02208 00000 00000 1 +1 1 529386 37.50 72 30 4 3 4 1 4 4 3 2 1 ? 3 5 60.00 6.80 ? ? 2 1 03205 00000 00000 2 +1 1 530612 36.50 100 24 3 3 3 1 3 3 3 3 1 ? 4 4 50.00 6.00 3 3.40 1 1 02208 00000 00000 1 +1 1 534618 37.2 40 20 ? ? ? ? ? ? ? ? ? ? 4 1 36 62 1 1 3 2 06112 00000 00000 2 diff --git a/data/horse-colic.names b/data/horse-colic.names new file mode 100755 index 0000000..066c9f5 --- /dev/null +++ b/data/horse-colic.names @@ -0,0 +1,267 @@ +1. TItle: Horse Colic database + +2. Source Information + -- Creators: Mary McLeish & Matt Cecile + Department of Computer Science + University of Guelph + Guelph, Ontario, Canada N1G 2W1 + mdmcleish@water.waterloo.edu + -- Donor: Will Taylor (taylor@pluto.arc.nasa.gov) + -- Date: 8/6/89 + +3. Past Usage: + -- Unknown + +4. Relevant Information: + + -- 2 data files + -- horse-colic.data: 300 training instances + -- horse-colic.test: 68 test instances + -- Possible class attributes: 24 (whether lesion is surgical) + -- others include: 23, 25, 26, and 27 + -- Many Data types: (continuous, discrete, and nominal) + +5. Number of Instances: 368 (300 for training, 68 for testing) + +6. Number of attributes: 28 + +7. Attribute Information: + + 1: surgery? + 1 = Yes, it had surgery + 2 = It was treated without surgery + + 2: Age + 1 = Adult horse + 2 = Young (< 6 months) + + 3: Hospital Number + - numeric id + - the case number assigned to the horse + (may not be unique if the horse is treated > 1 time) + + 4: rectal temperature + - linear + - in degrees celsius. + - An elevated temp may occur due to infection. + - temperature may be reduced when the animal is in late shock + - normal temp is 37.8 + - this parameter will usually change as the problem progresses + eg. may start out normal, then become elevated because of + the lesion, passing back through the normal range as the + horse goes into shock + 5: pulse + - linear + - the heart rate in beats per minute + - is a reflection of the heart condition: 30 -40 is normal for adults + - rare to have a lower than normal rate although athletic horses + may have a rate of 20-25 + - animals with painful lesions or suffering from circulatory shock + may have an elevated heart rate + + 6: respiratory rate + - linear + - normal rate is 8 to 10 + - usefulness is doubtful due to the great fluctuations + + 7: temperature of extremities + - a subjective indication of peripheral circulation + - possible values: + 1 = Normal + 2 = Warm + 3 = Cool + 4 = Cold + - cool to cold extremities indicate possible shock + - hot extremities should correlate with an elevated rectal temp. + + 8: peripheral pulse + - subjective + - possible values are: + 1 = normal + 2 = increased + 3 = reduced + 4 = absent + - normal or increased p.p. are indicative of adequate circulation + while reduced or absent indicate poor perfusion + + 9: mucous membranes + - a subjective measurement of colour + - possible values are: + 1 = normal pink + 2 = bright pink + 3 = pale pink + 4 = pale cyanotic + 5 = bright red / injected + 6 = dark cyanotic + - 1 and 2 probably indicate a normal or slightly increased + circulation + - 3 may occur in early shock + - 4 and 6 are indicative of serious circulatory compromise + - 5 is more indicative of a septicemia + + 10: capillary refill time + - a clinical judgement. The longer the refill, the poorer the + circulation + - possible values + 1 = < 3 seconds + 2 = >= 3 seconds + + 11: pain - a subjective judgement of the horse's pain level + - possible values: + 1 = alert, no pain + 2 = depressed + 3 = intermittent mild pain + 4 = intermittent severe pain + 5 = continuous severe pain + - should NOT be treated as a ordered or discrete variable! + - In general, the more painful, the more likely it is to require + surgery + - prior treatment of pain may mask the pain level to some extent + + 12: peristalsis + - an indication of the activity in the horse's gut. As the gut + becomes more distended or the horse becomes more toxic, the + activity decreases + - possible values: + 1 = hypermotile + 2 = normal + 3 = hypomotile + 4 = absent + + 13: abdominal distension + - An IMPORTANT parameter. + - possible values + 1 = none + 2 = slight + 3 = moderate + 4 = severe + - an animal with abdominal distension is likely to be painful and + have reduced gut motility. + - a horse with severe abdominal distension is likely to require + surgery just tio relieve the pressure + + 14: nasogastric tube + - this refers to any gas coming out of the tube + - possible values: + 1 = none + 2 = slight + 3 = significant + - a large gas cap in the stomach is likely to give the horse + discomfort + + 15: nasogastric reflux + - possible values + 1 = none + 2 = > 1 liter + 3 = < 1 liter + - the greater amount of reflux, the more likelihood that there is + some serious obstruction to the fluid passage from the rest of + the intestine + + 16: nasogastric reflux PH + - linear + - scale is from 0 to 14 with 7 being neutral + - normal values are in the 3 to 4 range + + 17: rectal examination - feces + - possible values + 1 = normal + 2 = increased + 3 = decreased + 4 = absent + - absent feces probably indicates an obstruction + + 18: abdomen + - possible values + 1 = normal + 2 = other + 3 = firm feces in the large intestine + 4 = distended small intestine + 5 = distended large intestine + - 3 is probably an obstruction caused by a mechanical impaction + and is normally treated medically + - 4 and 5 indicate a surgical lesion + + 19: packed cell volume + - linear + - the # of red cells by volume in the blood + - normal range is 30 to 50. The level rises as the circulation + becomes compromised or as the animal becomes dehydrated. + + 20: total protein + - linear + - normal values lie in the 6-7.5 (gms/dL) range + - the higher the value the greater the dehydration + + 21: abdominocentesis appearance + - a needle is put in the horse's abdomen and fluid is obtained from + the abdominal cavity + - possible values: + 1 = clear + 2 = cloudy + 3 = serosanguinous + - normal fluid is clear while cloudy or serosanguinous indicates + a compromised gut + + 22: abdomcentesis total protein + - linear + - the higher the level of protein the more likely it is to have a + compromised gut. Values are in gms/dL + + 23: outcome + - what eventually happened to the horse? + - possible values: + 1 = lived + 2 = died + 3 = was euthanized + + 24: surgical lesion? + - retrospectively, was the problem (lesion) surgical? + - all cases are either operated upon or autopsied so that + this value and the lesion type are always known + - possible values: + 1 = Yes + 2 = No + + 25, 26, 27: type of lesion + - first number is site of lesion + 1 = gastric + 2 = sm intestine + 3 = lg colon + 4 = lg colon and cecum + 5 = cecum + 6 = transverse colon + 7 = retum/descending colon + 8 = uterus + 9 = bladder + 11 = all intestinal sites + 00 = none + - second number is type + 1 = simple + 2 = strangulation + 3 = inflammation + 4 = other + - third number is subtype + 1 = mechanical + 2 = paralytic + 0 = n/a + - fourth number is specific code + 1 = obturation + 2 = intrinsic + 3 = extrinsic + 4 = adynamic + 5 = volvulus/torsion + 6 = intussuption + 7 = thromboembolic + 8 = hernia + 9 = lipoma/slenic incarceration + 10 = displacement + 0 = n/a + 28: cp_data + - is pathology data present for this case? + 1 = Yes + 2 = No + - this variable is of no significance since pathology data + is not included or collected for these cases + +8. Missing values: 30% of the values are missing \ No newline at end of file diff --git a/data/horse-colic.names.original b/data/horse-colic.names.original new file mode 100755 index 0000000..ced1f19 --- /dev/null +++ b/data/horse-colic.names.original @@ -0,0 +1,249 @@ +(Message inbox:6) +Received: from charon.arc.nasa.gov by ICS.UCI.EDU id aa10794; 6 Aug 89 16:05 PDT +Received: from HALEAKALA.arc.nasa.gov by CHARON.arc.nasa.gov via INTERNET with SMTP id 40376; 6 Aug 89 16:03:21 PDT +Date: Sun, 6 Aug 89 16:06 PDT +From: will taylor +Subject: Horse Colic DB - 1 of 3 +To: aha@ICS.UCI.EDU +Message-ID: <19890806230616.2.TAYLOR@HALEAKALA.arc.nasa.gov> + +Source of database: + + - Mary McLeish & Matt Cecile + Dept. of Computer Science + U. of Guelph + Guelph, Ontario, Canada N1G 2W1 + mdmcleish@water.waterloo.edu + +;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; + +Date: Sat, 5 Aug 89 09:40:08 EDT +From: mdmcleish@water.waterloo.edu +Message-Id: <8908051340.AA29845@water.waterloo.edu> +To: taylor@pluto.arc.nasa.gov + +HORSE COLIC DOMAIN: DESCRIPTION OF DATA +======================================= + +The data is supplied in two files. The first contains 300 horse +colic cases that should be used for training data while the second contains +68 cases that can be used for testing the performance of your method. + +The variable that we have tended to try and predict is V24, that is, whether +or not the lesion is surgical. Other variables of interest are outcome, V23, +and lesion types, V25,V26,V27. + +The sample contains approx. 30% missing values (indicated by a zero in the +data provided). You will need to deal with all types of variables (continuous, +discrete, and nominal) as well as the missing values in your method. + +VARIABLES: +========== +V1: surgery? + 1 = Yes, it had surgery + 2 = It was treated without surgery +V2: Age + 1 = Adult horse + 2 = Young (< 6 months) +V3: Hospital Number + - the case number assigned to the horse + (may not be unique if the horse is treated > 1 time) +V4: rectal temperature + - in degrees celsius. + - An elevated temp may occur due to infection. + - temperature may be reduced when the animal is in late shock + - normal temp is 37.8 + - this parameter will usually change as the problem progresses + eg. may start out normal, then become elevated because of + the lesion, passing back through the normal range as the + horse goes into shock +V5: pulse + - the heart rate in beats per minute + - is a reflection of the heart condition: 30 -40 is normal for adults + - rare to have a lower than normal rate although athletic horses + may have a rate of 20-25 + - animals with painful lesions or suffering from circulatory shock + may have an elevated heart rate +V6: respiratory rate + - normal rate is 8 to 10 + - usefulness is doubtful due to the great fluctuations +V7: temperature of extremities + - a subjective indication of peripheral circulation + - possible values: + 1 = Normal + 2 = Warm + 3 = Cool + 4 = Cold + - cool to cold extremities indicate possible shock + - hot extremities should correlate with an elevated rectal temp. +V8: peripheral pulse + - subjective + - possible values are: + 1 = normal + 2 = increased + 3 = reduced + 4 = absent + - normal or increased p.p. are indicative of adequate circulation + while reduced or absent indicate poor perfusion +V9: mucous membranes + - a subjective measurement of colour + - possible values are: + 1 = normal pink + 2 = bright pink + 3 = pale pink + 4 = pale cyanotic + 5 = bright red / injected + 6 = dark cyanotic + - 1 and 2 probably indicate a normal or slightly increased + circulation + - 3 may occur in early shock + - 4 and 6 are indicative of serious circulatory compromise + - 5 is more indicative of a septicemia +V10: capillary refill time + - a clinical judgement. The longer the refill, the poorer the + circulation + - possible values + 1 = < 3 seconds + 2 = >= 3 seconds +V11: pain + - a subjective judgement of the horse's pain level + - possible values: + 1 = alert, no pain + 2 = depressed + 3 = intermittent mild pain + 4 = intermittent severe pain + 5 = continuous severe pain + - should NOT be treated as a ordered or discrete variable! + - In general, the more painful, the more likely it is to require + surgery + - prior treatment of pain may mask the pain level to some extent +V12: peristalsis + - an indication of the activity in the horse's gut. As the gut + becomes more distended or the horse becomes more toxic, the + activity decreases + - possible values: + 1 = hypermotile + 2 = normal + 3 = hypomotile + 4 = absent +V13: abdominal distension + - An IMPORTANT parameter. + - possible values + 1 = none + 2 = slight + 3 = moderate + 4 = severe + - an animal with abdominal distension is likely to be painful and + have reduced gut motility. + - a horse with severe abdominal distension is likely to require + surgery just tio relieve the pressure +V14: nasogastric tube + - this refers to any gas coming out of the tube + - possible values: + 1 = none + 2 = slight + 3 = significant + - a large gas cap in the stomach is likely to give the horse + discomfort +V15: nasogastric reflux + - possible values + 1 = none + 2 = > 1 liter + 3 = < 1 liter + - the greater amount of reflux, the more likelihood that there is + some serious obstruction to the fluid passage from the rest of + the intestine +V16: nasogastric reflux PH + - scale is from 0 to 14 with 7 being neutral + - normal values are in the 3 to 4 range +V17: rectal examination - feces + - possible values + 1 = normal + 2 = increased + 3 = decreased + 4 = absent + - absent feces probably indicates an obstruction +V18: abdomen + - possible values + 1 = normal + 2 = other + 3 = firm feces in the large intestine + 4 = distended small intestine + 5 = distended large intestine + - 3 is probably an obstruction caused by a mechanical impaction + and is normally treated medically + - 4 and 5 indicate a surgical lesion +V19: packed cell volume + - the # of red cells by volume in the blood + - normal range is 30 to 50. The level rises as the circulation + becomes compromised or as the animal becomes dehydrated. +V20: total protein + - normal values lie in the 6-7.5 (gms/dL) range + - the higher the value the greater the dehydration +V21: abdominocentesis appearance + - a needle is put in the horse's abdomen and fluid is obtained from + the abdominal cavity + - possible values: + 1 = clear + 2 = cloudy + 3 = serosanguinous + - normal fluid is clear while cloudy or serosanguinous indicates + a compromised gut +V22: abdomcentesis total protein + - the higher the level of protein the more likely it is to have a + compromised gut. Values are in gms/dL +V23: outcome + - what eventually happened to the horse? + - possible values: + 1 = lived + 2 = died + 3 = was euthanized +V24: surgical lesion? + - retrospectively, was the problem (lesion) surgical? + - all cases are either operated upon or autopsied so that + this value and the lesion type are always known + - possible values: + 1 = Yes + 2 = No +V25,V26,V27: type of lesion + - first number is site of lesion + 1 = gastric + 2 = sm intestine + 3 = lg colon + 4 = lg colon and cecum + 5 = cecum + 6 = transverse colon + 7 = retum/descending colon + 8 = uterus + 9 = bladder + 11 = all intestinal sites + 00 = none + - second number is type + 1 = simple + 2 = strangulation + 3 = inflammation + 4 = other + - third number is subtype + 1 = mechanical + 2 = paralytic + 0 = n/a + - fourth number is specific code + 1 = obturation + 2 = intrinsic + 3 = extrinsic + 4 = adynamic + 5 = volvulus/torsion + 6 = intussuption + 7 = thromboembolic + 8 = hernia + 9 = lipoma/slenic incarceration + 10 = displacement + 0 = n/a +V28: cp_data + - is pathology data present for this case? + 1 = Yes + 2 = No + - this variable is of no significance since pathology data + is not included or collected for these cases + +;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; diff --git a/data/horse-colic.test b/data/horse-colic.test new file mode 100755 index 0000000..4111d21 --- /dev/null +++ b/data/horse-colic.test @@ -0,0 +1,68 @@ +2 1 528626 38.50 54 20 ? 1 2 2 3 4 1 2 2 5.90 ? 2 42.00 6.30 ? ? 1 2 03111 00000 00000 1 +2 1 527950 37.60 48 36 ? ? 1 1 ? 3 ? ? ? ? ? ? 44.00 6.30 1 5.00 1 2 03111 00000 00000 1 +1 1 535263 37.7 44 28 ? 4 3 2 5 4 4 1 1 ? 3 5 45 70 3 2 1 1 03205 00000 00000 2 +1 1 534523 37 56 24 3 1 4 2 4 4 3 1 1 ? ? ? 35 61 3 2 3 2 02205 02208 00000 2 +2 1 528926 38.00 42 12 3 ? 3 1 1 ? 1 ? ? ? ? 2 37.00 5.80 ? ? 1 2 03111 00000 00000 2 +1 1 534922 ? 60 40 3 ? 1 1 ? 4 ? 3 2 ? ? 5 42 72 ? ? 1 1 03111 00000 00000 2 +2 1 527642 38.40 80 60 3 2 2 1 3 2 1 2 2 ? 1 1 54.00 6.90 ? ? 1 2 00000 00000 00000 2 +2 1 5279821 37.80 48 12 2 1 2 1 3 ? 1 2 ? ? 2 ? 48.00 7.30 1 ? 1 2 00000 00000 00000 1 +? 1 534790 38.0 65 40 ? 1 4 2 2 ? ? ? ? ? ? 5 ? ? ? ? ? 1 03111 03205 00000 2 +2 1 5275211 37.90 45 36 3 3 3 2 2 3 1 2 1 ? 3 ? 33.00 5.70 3 ? 1 1 02205 00000 00000 1 +2 1 5278332 39.00 84 12 3 1 5 1 2 4 2 1 2 7.00 ? 4 62.00 5.90 2 2.20 2 1 02208 00000 00000 1 +2 1 528959 38.20 60 24 3 1 3 2 3 3 2 3 3 ? 4 4 53.00 7.50 2 1.40 1 2 01124 00000 00000 1 +1 1 534921 ? 140 ? ? ? 4 2 5 4 4 1 1 ? ? 5 30 69 ? ? 2 2 06112 00000 00000 2 +1 1 528999 37.90 120 60 3 3 3 1 5 4 4 2 2 7.50 4 5 52.00 6.60 3 1.80 2 1 03205 00000 00000 1 +2 1 528067 38.00 72 36 1 1 3 1 3 ? 2 2 1 ? 3 5 38.00 6.80 2 2.00 1 2 03124 00000 00000 1 +2 9 5291329 38.00 92 28 1 1 2 1 1 3 2 3 ? 7.20 ? ? 37.00 6.10 1 1.10 1 2 00000 00000 00000 1 +1 1 529478 38.30 66 30 2 3 1 1 2 4 3 3 2 8.50 4 5 37.00 6.00 ? ? 1 1 05111 00000 00000 2 +2 1 529991 37.50 48 24 3 1 1 1 2 1 ? 1 1 ? 3 2 43.00 6.00 1 2.80 1 2 07111 00000 00000 1 +1 1 530033 37.50 88 20 2 3 3 1 4 3 3 ? ? ? ? ? 35.00 6.40 1 ? 2 1 02205 00000 00000 2 +2 9 5299049 ? 150 60 4 4 4 2 5 4 4 ? ? ? ? ? ? ? ? ? 2 1 01400 00000 00000 2 +1 1 534497 39.7 100 30 ? ? 6 2 4 4 3 1 ? ? 4 5 65 75 ? ? 3 1 03205 00000 00000 2 +1 1 528369 38.30 80 ? 3 3 4 2 5 4 3 2 1 ? 4 4 45.00 7.50 2 4.60 1 1 03209 00000 00000 1 +2 1 530107 37.50 40 32 3 1 3 1 3 2 3 2 1 ? ? 5 32.00 6.40 1 1.10 1 1 03124 00000 00000 1 +1 1 530239 38.40 84 30 3 1 5 2 4 3 3 2 3 6.50 4 4 47.00 7.50 3 ? 2 1 06111 00000 00000 2 +1 1 530505 38.10 84 44 4 ? 4 2 5 3 1 1 3 5.00 ? 4 60.00 6.80 ? 5.70 2 1 02209 00000 00000 1 +2 1 529567 38.70 52 ? 1 1 1 1 1 3 1 ? ? ? 1 3 4.00 74.00 ? ? 1 2 00000 00000 00000 2 +2 1 529597 38.10 44 40 2 1 3 1 3 3 1 ? ? ? 1 3 35.00 6.80 ? ? 1 2 00000 00000 00000 2 +2 1 534429 38.4 52 20 2 1 3 1 1 3 2 2 1 ? 3 5 41 63 1 1 1 2 00000 00000 00000 2 +1 1 529629 38.20 60 ? 1 ? 3 1 2 1 1 1 1 ? 4 4 43.00 6.20 2 3.90 1 1 02206 00000 00000 1 +2 1 528382 37.70 40 18 1 1 1 ? 3 2 1 1 1 ? 3 3 36.00 3.50 ? ? 1 2 00400 00000 00000 2 +1 1 534898 39.1 60 10 ? 1 1 ? 2 3 ? ? ? ? 4 4 ? ? ? ? 1 1 02113 00000 00000 2 +2 1 529615 37.80 48 16 1 1 1 1 ? 1 1 2 1 ? 4 3 43.00 7.50 ? ? 1 2 00000 00000 00000 2 +1 1 526090 39.00 120 ? 4 3 5 2 2 4 3 2 3 8.00 ? ? 65.00 8.20 3 4.60 1 2 05110 00000 00000 2 +1 1 529765 38.20 76 ? 2 3 2 1 5 3 3 1 2 6.00 1 5 35.00 6.50 2 0.90 1 1 03205 00000 00000 1 +2 1 528310 38.30 88 ? ? ? 6 ? ? ? ? ? ? ? ? ? ? ? ? ? 2 2 02300 00000 00000 2 +1 1 529925 38.00 80 30 3 3 3 1 ? ? ? ? ? 6.00 ? ? 48.00 8.30 ? 4.30 1 1 02111 00000 00000 2 +1 1 527807 ? ? ? 3 1 1 1 2 3 3 1 3 6.00 4 4 ? ? 2 ? 2 1 02113 00000 00000 1 +1 1 5281441 37.60 40 ? 1 1 1 1 1 1 1 ? ? ? 1 1 ? ? 2 2.10 1 1 31110 00000 00000 1 +2 1 530695 37.50 44 ? 1 1 1 1 3 3 2 ? ? ? ? ? 45.00 5.80 2 1.40 1 2 03111 00000 00000 1 +2 1 533889 38.2 42 16 1 1 3 1 1 3 1 ? ? ? 1 ? 35 60 1 1 1 2 00000 00000 00000 2 +2 1 533815 38 56 44 3 3 3 ? ? 1 1 2 1 ? 4 ? 47 70 2 1 1 2 00000 00000 00000 2 +2 1 527664 38.30 45 20 3 3 2 2 2 4 1 2 ? ? 4 ? ? ? ? ? 1 2 00000 00000 00000 2 +1 1 5262542 ? 48 96 1 1 3 1 ? 4 1 2 1 ? 1 4 42.00 8.00 1 ? 1 1 02208 00000 00000 2 +1 1 528268 37.70 55 28 2 1 2 1 2 3 3 ? 3 5.00 4 5 ? ? ? ? 1 1 03209 00000 00000 2 +2 1 528919 36.00 100 20 4 3 6 2 2 4 3 1 1 ? 4 5 74.00 5.70 2 2.50 3 1 03205 00000 00000 1 +1 1 527494 37.10 60 20 2 ? 4 1 3 ? 3 ? 2 5.00 3 4 64.00 8.50 2 ? 1 1 07111 00000 00000 1 +2 1 529980 37.10 114 40 3 ? 3 2 2 2 1 ? ? ? ? 3 32.00 ? 3 6.50 1 2 00400 00000 00000 2 +1 1 533954 38.1 72 30 3 3 3 1 4 4 3 2 1 ? 3 5 37 56 3 1 1 1 04206 00000 00000 2 +1 1 5281092 37.00 44 12 3 1 1 2 1 1 1 ? ? ? 4 2 40.00 6.70 3 8.00 1 1 02208 00000 00000 2 +1 1 534686 38.6 48 20 3 1 1 1 4 3 1 ? ? ? 3 ? 37 75 ? ? 1 1 03111 00000 00000 2 +1 1 534475 ? 82 72 3 1 4 1 2 3 3 ? 3 ? 4 4 53 65 3 2 3 1 02209 03205 00000 2 +1 9 5274919 38.20 78 60 4 4 6 ? 3 3 3 ? ? ? 1 ? 59.00 5.80 3 3.10 2 1 01400 00000 00000 1 +2 1 533815 37.8 60 16 1 1 3 1 2 3 2 1 2 ? 3 ? 41 73 ? ? 3 2 04124 00000 00000 2 +1 1 534156 38.7 34 30 2 ? 3 1 2 3 ? ? ? ? ? ? 33 69 ? 2 3 1 07113 00000 00000 2 +1 1 514279 ? 36 12 1 1 1 1 1 2 1 1 1 ? 1 5 44.00 ? ? ? 1 1 31110 00000 00000 1 +2 1 528433 38.30 44 60 ? ? 1 1 ? ? ? ? ? ? ? ? 6.40 36.00 ? ? 1 1 00000 00000 00000 2 +2 1 527465 37.40 54 18 3 ? 1 1 3 4 3 2 2 ? 4 5 30.00 7.10 2 ? 1 1 07111 00000 00000 1 +1 1 534268 ? ? ? 4 3 ? 2 2 4 1 ? ? ? ? ? 54 76 3 2 1 1 08405 00000 00000 2 +1 1 535337 36.6 48 16 3 1 3 1 4 1 1 1 1 ? ? ? 27 56 ? ? 3 1 04206 00000 00000 2 +1 1 534111 38.5 90 ? 1 1 3 1 3 3 3 2 3 2 4 5 47 79 ? ? 1 1 06112 00000 00000 2 +1 1 530576 ? 75 12 1 1 4 1 5 3 3 ? 3 5.80 ? ? 58.00 8.50 1 ? 1 1 02209 00000 00000 1 +2 1 529930 38.20 42 ? 3 1 1 1 1 1 2 2 1 ? 3 2 35.00 5.90 2 ? 1 2 03113 00000 00000 2 +1 9 5274919 38.20 78 60 4 4 6 ? 3 3 3 ? ? ? 1 ? 59.00 5.80 3 3.10 2 1 02205 00000 00000 1 +2 1 529695 38.60 60 30 1 1 3 1 4 2 2 1 1 ? ? ? 40.00 6.00 1 ? 1 1 03205 00000 00000 2 +2 1 528452 37.80 42 40 1 1 1 1 1 3 1 ? ? ? 3 3 36.00 6.20 ? ? 1 2 04124 00000 00000 2 +1 1 534783 38 60 12 1 1 2 1 2 1 1 1 1 ? 1 4 44 65 3 2 3 1 02209 00000 00000 2 +2 1 528926 38.00 42 12 3 ? 3 1 1 1 1 ? ? ? ? 1 37.00 5.80 ? ? 1 2 03111 00000 00000 2 +2 1 530670 37.60 88 36 3 1 1 1 3 3 2 1 3 1.50 ? ? 44.00 6.00 ? ? 2 1 02112 00000 00000 2 diff --git a/function.py b/function.py new file mode 100644 index 0000000..409b1ac --- /dev/null +++ b/function.py @@ -0,0 +1,83 @@ +# function.py +import numpy as np + +""" +实验说明: +- 自行编写实现数据加载与预测病马死亡的对率回归算法。 + +注意事项: +- 在 function.py 中实现对率回归算法。 +- 可以自行导入其他库,需要在 requirements.txt 添加依赖,若未在 requirements.txt 中添加使用到的依赖,则无法自动评测,成绩为零。 +- 自动评测脚本仅会加载 train_logreg、predict_logreg 和 load_data 函数,请勿修改函数名。 + +测评环境: +- CPU: Intel Xeon(R) CPU E3-1231 v3 @ 3.40GHz +- OS: Ubuntu 22.04.4 LTS +- Python: 3.10.12 +- numpy: 2.1.1 +""" + + +""" +请在这里填写学号和姓名,不填写即成绩无效。 +""" +id = "202210423xxx" +name = "test_name" + + +# 这里写自己的代码实现 +def train_logreg(X, y, other_params="你自己设置一些其它参数"): + """ + 对率回归训练函数。 + + Args: + - X (numpy array): 特征数据。 + - y (numpy array): 标签数据。 + - other_params (str): 其它参数,可选设置。若需设置其它参数,必须设置其默认值,否则将**无法通过**自动评测,**成绩为零**。 + + Returns: + - numpy array: 训练得到的权重。 + """ + + +def predict_logreg(inX, weights): + """ + 对率回归预测函数。 + + Args: + - inX (numpy array): 输入待分类的样本。 + - weights (numpy array): 训练得到的权重。 + + Returns: + - int: 预测的分类标签。 + """ + + +# 这里也写自己的代码实现 +def load_data(filepath): + """ + 从文件中加载数据,若不自行正确实现,则无法通过评测,**不记录成绩**。 + + Args: + - directory (str): 数据文件路径。 + + Returns: + - np.array: 特征数据。 + - np.array: 标签数据。 + """ + + +if __name__ == "__main__": + # 以下代码可用于测试,可自行随意修改 + # 加载训练集 + X_train, y_train = load_data("./data/horse-colic.data") + + # 加载测试集 + X_test, y_test = load_data("./data/horse-colic.test") + + # 训练对率回归模型 + weights = train_logreg(X_train, y_train, learning_rate=0.01, iterations=1000) + + # 测试单个数据 + y_pred = predict_logreg(X_test[11], weights) + print(f"预测结果: {y_pred}, 实际结果: {y_test[11]}") diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000..4bb300f --- /dev/null +++ b/requirements.txt @@ -0,0 +1,2 @@ +numpy==2.1.1 +requests==2.32.3