{"id":621,"date":"2024-07-11T07:03:00","date_gmt":"2024-07-10T23:03:00","guid":{"rendered":"http:\/\/123.60.176.65\/?p=621"},"modified":"2024-07-11T07:03:00","modified_gmt":"2024-07-10T23:03:00","slug":"%e6%89%8b%e6%8a%8a%e6%89%8b%e6%95%99%e4%bd%a0ai%e9%a1%be%e6%8a%95%ef%bc%9aai%e5%af%b9%e8%82%a1%e7%a5%a8%e5%9b%9e%e6%8a%a5%e7%9a%84%e7%b2%be%e5%87%86%e9%a2%84%e6%b5%8b%ef%bc%88%e8%bf%90%e7%94%a8-cfc-sa","status":"publish","type":"post","link":"https:\/\/laoyulaoyu.com\/index.php\/2024\/07\/11\/%e6%89%8b%e6%8a%8a%e6%89%8b%e6%95%99%e4%bd%a0ai%e9%a1%be%e6%8a%95%ef%bc%9aai%e5%af%b9%e8%82%a1%e7%a5%a8%e5%9b%9e%e6%8a%a5%e7%9a%84%e7%b2%be%e5%87%86%e9%a2%84%e6%b5%8b%ef%bc%88%e8%bf%90%e7%94%a8-cfc-sa\/","title":{"rendered":"\u624b\u628a\u624b\u6559\u4f60ai\u987e\u6295\uff1aAI\u5bf9\u80a1\u7968\u56de\u62a5\u7684\u7cbe\u51c6\u9884\u6d4b\uff08\u8fd0\u7528 CFC SageMaker \u7b97\u6cd5\u7684 LNN\uff09"},"content":{"rendered":"<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img decoding=\"async\" src=\"http:\/\/123.60.176.65\/wp-content\/uploads\/2024\/07\/441d464c2c7b5891678b1c4e05454089_1720055459399917875.pngtplv-a9rns2rl98-web-thumb.webp\" alt=\"\" class=\"wp-image-646\"\/><\/figure>\n<\/div>\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<pre class=\"wp-block-verse\"><strong>\u5199\u5728\u524d\u9762\u7684\u8bdd\uff1a<\/strong>\u5b66\u672f\u7814\u7a76\u8005\u4e0e\u884c\u4e1a\u4ece\u4e1a\u8005\u59cb\u7ec8\u9488\u5bf9<mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-vivid-cyan-blue-color\">\u80a1\u7968\u56de\u62a5\u9884\u6d4b\u5c55<\/mark>\u5f00\u4e86\u5e7f\u6cdb\u63a2\u7a76\u3002\u4e3a\u6b64\uff0c\u4ed6\u4eec\u63d0\u51fa\u4e86\u591a\u79cd\u4ece\u7b80\u5355\u7ebf\u6027\u56de\u5f52\u81f3\u590d\u6742\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u7684\u673a\u5668\u5b66\u4e60\u6a21\u578b\u3002\u5728\u672c\u6587\u4e2d\uff0c\u6211\u4eec<mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-vivid-cyan-blue-color\">\u4e3b\u8981\u5229\u7528\u6db2\u4f53\u795e\u7ecf\u7f51\u7edc\uff08LNN\uff09\u7684\u6027\u80fd\uff0c\u8fd9\u662f\u4e00\u79cd\u7528\u4ee5\u5904\u7406\u5e8f\u5217\u6570\u636e\u7684\u65b0\u578b\u795e\u7ecf\u7f51\u7edc\u67b6\u6784\u3002<\/mark><\/pre>\n<\/blockquote>\n\n\n\n<p>LNN \u5c5e\u4e8e\u8fde\u7eed\u65f6\u95f4\u5faa\u73af\u795e\u7ecf\u7f51\u7edc\uff08CT-RNN\uff09\uff0c\u5176\u9690\u85cf\u72b6\u6001\u968f\u65f6\u95f4\u6f14\u5316\u7684\u8fc7\u7a0b\u88ab\u5efa\u6a21\u4e3a\u5e38\u5fae\u5206\u65b9\u7a0b\uff08ODE\uff09\u3002LNN \u57fa\u4e8e\u6db2\u4f53\u65f6\u95f4\u5e38\u6570\uff08LTC\uff09\u5e38\u5fae\u5206\u65b9\u7a0b\uff0c\u5176\u9690\u85cf\u72b6\u6001\u7684\u5bfc\u6570\u548c\u65f6\u95f4\u5e38\u6570\u5747\u901a\u8fc7\u795e\u7ecf\u7f51\u7edc\u8fdb\u884c\u5efa\u6a21\u3002<\/p>\n\n\n\n<p>\u672c\u6587\u5c06\u91cd\u70b9\u9610\u8ff0\u95ed\u5408\u5f62\u5f0f\u7684\u8fde\u7eed\u6df1\u5ea6\uff08CfC\uff09\u7f51\u7edc\u3002CfC \u7f51\u7edc\u901a\u8fc7\u5b9e\u73b0 LTC \u5e38\u5fae\u5206\u65b9\u7a0b\u7684\u8fd1\u4f3c\u95ed\u5f0f\u89e3\uff0c\u4e0e\u5176\u4ed6 CT-RNN\uff08\u5305\u62ec LTC\uff09\u76f8\u6bd4\uff0c\u80fd\u591f\u8fbe\u6210\u66f4\u8fc5\u901f\u7684\u8bad\u7ec3\u548c\u63a8\u7406\u6027\u80fd\uff0c\u56e0\u540e\u8005\u9700\u8981\u8fd0\u7528\u6570\u503c\u6c42\u89e3\u5668\u53bb\u6c42\u89e3\u5e38\u5fae\u5206\u65b9\u7a0b\u3002<\/p>\n\n\n\n<p>\u6211\u4eec\u4f1a\u8fd0\u7528\u7531 Amazon sageMaker \u5b9e\u73b0\u7684 CfC \u7f51\u7edc\u8fdb\u884c\u6982\u7387\u65f6\u95f4\u5e8f\u5217\u9884\u6d4b\uff0c\u4e5f\u5373 CfC SageMaker \u7b97\u6cd5\u3002\u6211\u4eec\u5c06\u4f7f\u7528\u6807\u51c6\u666e\u5c14 500 \u6307\u6570\u7684\u5df2\u5b9e\u73b0\u6ce2\u52a8\u7387\u4ee5\u53ca\u4e0d\u540c\u7684\u9690\u542b\u6ce2\u52a8\u7387\u6307\u6570\u5f53\u4f5c\u8f93\u5165\uff0c\u4ee5\u9884\u6d4b\u6807\u51c6\u666e\u5c14 500 \u6307\u6570 30 \u5929\u56de\u62a5\u7684\u6761\u4ef6\u5747\u503c\u548c\u6761\u4ef6\u6807\u51c6\u5dee\u3002<\/p>\n\n\n\n<p>\u6211\u4eec\u5c06\u8fd0\u7528 2022 \u5e74 6 \u6708 30 \u65e5\u81f3 2024 \u5e74 6 \u6708 28 \u65e5\u7684\u6bcf\u65e5\u6536\u76d8\u4ef7\u6570\u636e\uff0c\u8fd9\u4e9b\u6570\u636e\u4f1a\u4ece\u96c5\u864e\u8d22\u7ecf\u8fdb\u884c\u4e0b\u8f7d\u3002\u6a21\u578b\u5c06\u57fa\u4e8e\u622a\u81f3 2023 \u5e74 9 \u6708 8 \u65e5\u7684\u6570\u636e\u5c55\u5f00\u8bad\u7ec3\uff0c\u5e76\u8fd0\u7528\u8bad\u7ec3\u597d\u7684\u6a21\u578b\u9884\u6d4b\u622a\u81f3 2024 \u5e74 6 \u6708 28 \u65e5\u7684\u540e\u7eed\u6570\u636e\u3002\u7ed3\u679c\u8868\u660e\uff0cCfC SageMaker \u7b97\u6cd5\u5b9e\u73b0\u4e86 1.4%\u7684\u5e73\u5747\u7edd\u5bf9\u8bef\u5dee\u4ee5\u53ca 95.8%\u7684\u5e73\u5747\u65b9\u5411\u51c6\u786e\u7387\u3002<\/p>\n\n\n\n<p><strong>1.\u6a21\u578b\u8f93\u51fa<\/strong>\u5373\u4e3a\u6807\u51c6\u666e\u5c14 500 \u6307\u6570\u7684 30 \u5929\u56de\u62a5\u7387\uff0c\u5176\u8ba1\u7b97\u65b9\u5f0f\u5982\u4e0b\uff1a<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img decoding=\"async\" src=\"http:\/\/123.60.176.65\/wp-content\/uploads\/2024\/07\/640.png\" alt=\"\" class=\"wp-image-623\"\/><\/figure>\n<\/div>\n\n\n<p>\u5bf9\u4e8e\u6bcf\u4e00\u5929 t\uff0c\u5176\u4e2d P\uff08t\uff09\u4e3a\u6807\u51c6\u666e\u5c14 500 \u6307\u6570\u5728\u7b2c t \u5929\u7684\u6536\u76d8\u4ef7\u3002\u6211\u4eec\u5c06\u8fd0\u7528 30 \u5929\u7684\u9884\u6d4b\u957f\u5ea6\uff0c\u8fd9\u610f\u5473\u7740\u6a21\u578b\u5c06\u8f93\u51fa\u968f\u540e 30 \u5929\u7684 30 \u5929\u56de\u62a5\u3002\u5047\u8bbe\u6211\u4eec\u8fd0\u7528\u91cd\u53e0\uff08\u6216\u6eda\u52a8\uff09\u56de\u62a5\uff0c\u4ece\u7b2c t \u5929\u81f3\u7b2c t \u5929 + 30 \u7684\u9884\u6d4b 30 \u5929\u56de\u62a5\u5373\u4e3a\u8f93\u51fa\u5e8f\u5217\u4e2d\u7684\u6700\u540e\u4e00\u4e2a\u56de\u62a5\u3002<\/p>\n\n\n\n<p><strong>2.\u8f93\u5165\u65b9\u9762<\/strong>\uff0c\u8be5\u6a21\u578b\u4f7f\u7528\u6807\u51c6\u666e\u5c14 500 \u6307\u6570\u8fc7\u53bb 30 \u5929\u7684\u56de\u62a5\u7387\u4ee5\u53ca\u4e0b\u5217\u6ce2\u52a8\u7387\u6307\u6807\u7684\u8fc7\u53bb\u503c\uff1a<\/p>\n\n\n\n<p>RVOL\uff1a\u6807\u51c6\u666e\u5c14 500 \u6307\u6570\u7684\u5b9e\u9645\u6ce2\u52a8\u7387\uff0c\u901a\u8fc7\u8ba1\u7b97\u6807\u51c6\u666e\u5c14 500 \u6307\u6570\u6bcf\u65e5\u56de\u62a5\u7684 30 \u5929\u6eda\u52a8\u6837\u672c\u6807\u51c6\u5dee\u5f97\u51fa\u3002<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>VIX\u6307\u6570\uff1a\u7528\u4e8e\u8861\u91cf\u6807\u51c6\u666e\u5c14 500 \u671f\u6743\u7684 30 \u5929\u9690\u542b\u6ce2\u52a8\u7387\u3002<\/li>\n\n\n\n<li>VVIX\u6307\u6570\uff1a\u53cd\u6620 VIX \u7684 30 \u5929\u9884\u671f\u6ce2\u52a8\u7387\u3002<\/li>\n\n\n\n<li>VXN\u6307\u6570\uff1a\u7528\u4e8e\u8861\u91cf\u7eb3\u65af\u8fbe\u514b 100 \u671f\u6743\u7684 30 \u5929\u9690\u542b\u6ce2\u52a8\u7387\u3002<\/li>\n\n\n\n<li>GVZ \u6307\u6570\uff1a\u7528\u4e8e\u8861\u91cf SPDR \u9ec4\u91d1\u80a1\u7968 ETF\uff08GLD\uff09\u671f\u6743 30 \u5929\u9690\u542b\u6ce2\u52a8\u7387\u3002<\/li>\n\n\n\n<li>OVX\u6307\u6570\uff1a\u7528\u4e8e\u8861\u91cf\u7f8e\u56fd\u77f3\u6cb9\u57fa\u91d1\uff08USO\uff09\u671f\u6743\u7684 30 \u5929\u9690\u542b\u6ce2\u52a8\u7387\u3002<\/li>\n<\/ul>\n\n\n\n<p>RVOL \u5c5e\u4e8e\u5411\u540e\u770b\u7684\u6307\u6807\uff0c\u56e0\u5176\u4f30\u8ba1\u4e86\u8fc7\u53bb 30 \u5929\u7684\u6ce2\u52a8\u7387\uff0c\u800c VIX\u3001VVIX\u3001VXN\u3001GVZ \u4ee5\u53ca OVX \u5747\u4e3a\u524d\u77bb\u6027\u6307\u6807\uff0c\u56e0\u5176\u53cd\u6620\u4e86\u5e02\u573a\u5bf9\u672a\u6765 30 \u5929\u6ce2\u52a8\u7387\u7684\u9884\u671f\u3002<\/p>\n\n\n\n<p>\u6211\u4eec\u5c06\u8fd0\u7528 30 \u5929\u7684\u4e0a\u4e0b\u6587\u957f\u5ea6\uff0c\u4e5f\u5c31\u662f\u8bf4\uff0c\u8be5\u6a21\u578b\u5c06\u8fd0\u7528 30 \u5929\u7684\u56de\u62a5\u7387\u4ee5\u53ca\u8fc7\u53bb 30 \u5929\u7684\u6ce2\u52a8\u7387\u6307\u6807\u5f53\u4f5c\u8f93\u5165\uff0c\u4ee5\u9884\u6d4b\u968f\u540e 30 \u5929\u7684 30 \u5929\u56de\u62a5\u7387\u3002<\/p>\n\n\n\n<p><strong>3.\u73af\u5883\u8bbe\u7f6e<\/strong><\/p>\n\n\n\n<p>\u9996\u5148\u5bfc\u5165\u6240\u6709\u4f9d\u8d56\u9879\u5e76\u8bbe\u7f6e SageMaker \u73af\u5883\u3002<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code><code>import io<\/code><code>import sagemaker<\/code><code>import pandas as pd<\/code><code>import numpy as np<\/code><code>import matplotlib.pyplot as plt<\/code><code>import yfinance as yf<\/code><code>from sklearn.metrics import root_mean_squared_error, mean_absolute_error, accuracy_score, f1_score<\/code><code><br><\/code><code><em># SageMaker session<\/em><\/code><code>sagemaker_session = sagemaker.Session()<\/code><code><em># SageMaker role<\/em><\/code><code>role = sagemaker.get_execution_role()<\/code><code><em># S3 bucket<\/em><\/code><code>bucket = sagemaker_session.default_bucket()<\/code><code><em># EC2 instance<\/em><\/code><code>instance_type = \"ml.m5.4xlarge\"<\/code><\/code><\/pre>\n\n\n\n<p>\u5176\u540e\uff0c\u6211\u4eec\u660e\u786e\u795e\u7ecf\u7f51\u7edc\u7684\u4e0a\u4e0b\u6587\u957f\u5ea6\u4e0e\u9884\u6d4b\u957f\u5ea6\u3002\u4e0a\u4e0b\u6587\u957f\u5ea6\u5373\u4e3a\u7528\u4f5c\u8f93\u5165\u7684\u8fc7\u53bb\u65f6\u95f4\u6b65\u957f\u6570\u91cf\uff0c\u800c\u9884\u6d4b\u957f\u5ea6\u5373\u4e3a\u8981\u9884\u6d4b\u7684\u672a\u6765\u65f6\u95f4\u6b65\u957f\u6570\u91cf\u3002\u6211\u4eec\u5c06\u4e24\u8005\u5747\u8bbe\u5b9a\u4e3a\u7b49\u540c\u4e8e 30 \u5929\uff0c\u4e5f\u5c31\u662f\u8bf4\uff0c\u6211\u4eec\u8fd0\u7528\u8f93\u5165\u4e0e\u8f93\u51fa\u7684\u524d 30 \u4e2a\u503c\u53bb\u9884\u6d4b\u8f93\u51fa\u7684\u540e\u7eed 30 \u4e2a\u503c\u3002<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><\/li>\n<\/ul>\n\n\n\n<pre class=\"wp-block-code\"><code><code>context_length&nbsp;=&nbsp;30<\/code><code>prediction_length = 30<\/code><\/code><\/pre>\n\n\n\n<p>\u6211\u4eec\u8fd8\u660e\u786e\u4e86 CfC \u7f51\u7edc\u7684\u6240\u6709\u5176\u4f59\u8d85\u53c2\u6570\u3002\u9700\u6ce8\u610f\uff0c\u6211\u4eec\u8fd0\u7528\u53c2\u6570\u5c0f\u4e8e 5k \u7684\u76f8\u5bf9\u8f83\u5c0f\u7684\u6a21\u578b\u3002<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code><code>hyperparameters = {<\/code><code>    \"context-length\": context_length,<\/code><code>    \"prediction-length\": prediction_length,<\/code><code>    \"sequence-stride\": 1,<\/code><code>    \"hidden-size\": 20,<\/code><code>    \"backbone-layers\": 1,<\/code><code>    \"backbone-units\": 40,<\/code><code>    \"backbone-activation\": \"lecun\",<\/code><code>    \"backbone-dropout\": 0,<\/code><code>    \"minimal\": True,<\/code><code>    \"no-gate\": True,<\/code><code>    \"use-mixed\": False,<\/code><code>    \"use-ltc\": False,<\/code><code>    \"batch-size\": 32,<\/code><code>    \"lr\": 0.0001,<\/code><code>    \"lr-decay\": 0.9999,<\/code><code>    \"epochs\": 800,<\/code><code>}<\/code><\/code><\/pre>\n\n\n\n<p><strong>4.\u6570\u636e\u51c6\u5907<\/strong><\/p>\n\n\n\n<p>\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u8fd0\u7528 Yahoo\uff01Finance Python API \u4ece Yahoo\uff01Finance \u4e0b\u8f7d 2022 \u5e74 6 \u6708 30 \u65e5\u81f3 2024 \u5e74 6 \u6708 28 \u65e5\u7684\u6bcf\u65e5\u6536\u76d8\u4ef7\u65f6\u95f4\u5e8f\u5217\u3002<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code><code>tickers = &#91;\"^SPX\", \"^VIX\", \"^VVIX\", \"^VXN\", \"^GVZ\", \"^OVX\"]<\/code><code>dataset = yf.download(\" \".join(tickers), start=\"2022-06-30\", end=\"2024-06-29\")<\/code><code>dataset = dataset.loc&#91;:, dataset.columns.get_level_values(0) == \"Close\"]<\/code><code>dataset.columns = dataset.columns.get_level_values(1)<\/code><code>dataset.ffill(inplace=True)<\/code><\/code><\/pre>\n\n\n\n<p>\u968f\u540e\uff0c\u6211\u4eec\u8ba1\u7b97\u6807\u51c6\u666e\u5c14 500 \u6307\u6570\u7684 30 \u5929\u56de\u62a5\u7387\u4ee5\u53ca 30 \u5929\u7684\u5b9e\u9645\u6ce2\u52a8\u7387\u3002<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code># calculate the returns\ndataset&#91;\"Return30\"] = np.log(dataset&#91;\"^SPX\"]).diff(periods=30)\n# calculate the realized volatility\ndataset&#91;\"RVOL\"] = np.log(dataset&#91;\"^SPX\"]).diff(periods=1).rolling(window=30).std(ddof=1)\n# drop the prices\ndataset.drop(labels=&#91;\"^SPX\"], axis=1, inplace=True)\n# drop the missing values\ndataset.dropna(inplace=True)\n# move the returns to the first column\ndataset = dataset&#91;&#91;\"Return30\"] + dataset.columns.drop(\"Return30\").tolist()]<\/code><\/pre>\n\n\n\n<p>\u8be5\u6570\u636e\u96c6\u6db5\u76d6 502 \u4e2a\u6bcf\u65e5\u89c2\u6d4b\u503c\uff0c\u5728\u53bb\u9664\u56e0\u8ba1\u7b97\u6536\u76ca\u548c\u5df2\u5b9e\u73b0\u6ce2\u52a8\u7387\u800c\u4ea7\u751f\u7684\u7f3a\u5931\u503c\u540e\uff0c\u8fd9\u4e9b\u89c2\u6d4b\u503c\u51cf\u5c11\u81f3 472 \u4e2a\u3002<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large\"><img decoding=\"async\" src=\"http:\/\/123.60.176.65\/wp-content\/uploads\/2024\/07\/640-6-569x1024.webp\" alt=\"\" class=\"wp-image-624\"\/><\/figure>\n<\/div>\n\n\n<p>2022-08-12 \u81f3 2024-06-28 \u7684 30 \u5929\u56de\u62a5\u300130 \u5929\u5b9e\u9645\u6ce2\u52a8\u7387\u4ee5\u53ca\u6ce2\u52a8\u7387\u6307\u6570\u3002<\/p>\n\n\n\n<p>\u6211\u4eec\u7ee7\u7eed\u4f9d\u7167 CfC SageMaker \u7b97\u6cd5\u9884\u671f\u7684\u683c\u5f0f\u91cd\u547d\u540d\u5217\uff0c\u5176\u4e2d\u8f93\u51fa\u540d\u79f0\u5e94\u4ee5 \u5f00\u5934\uff0c\u8f93\u5165\u540d\u79f0\u5e94\u4ee5 \u5f00\u5934\u3002<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>dataset.columns = &#91;\"y\"] + &#91;f\"x{i}\" for i in range(dataset.shape&#91;1] - 1)]<\/code><\/pre>\n\n\n\n<p>\u8bf7\u6ce8\u610f\uff0c\u7b97\u6cd5\u7684\u4ee3\u7801\u59cb\u7ec8\u5728\u8f93\u5165\u4e2d\u5305\u542b\u8f93\u51fa\u7684\u8fc7\u53bb\u503c\uff0c\u6240\u4ee5\u5728\u4e3a\u6a21\u578b\u51c6\u5907\u6570\u636e\u65f6\u65e0\u9700\u6dfb\u52a0\u8f93\u51fa\u7684\u6ede\u540e\u503c\u3002<\/p>\n\n\n\n<p><strong>5.\u6d4b\u8bd5<\/strong><\/p>\n\n\n\n<p>\u4e3a\u4e86\u9a8c\u8bc1\u6a21\u578b\uff0c\u6211\u4eec\u5c06\u6570\u636e\u62c6\u5206\u4e3a\u8bad\u7ec3\u96c6\u4e0e\u6d4b\u8bd5\u96c6\u3002\u8bad\u7ec3\u96c6\u5305\u542b\u524d 70%\u7684\u6570\u636e\uff0c\u800c\u6d4b\u8bd5\u96c6\u5305\u542b\u6700\u540e 30%\u7684\u6570\u636e\u3002\u9700\u6ce8\u610f\uff0c\u6570\u636e\u7531\u7b97\u6cd5\u5728\u5185\u90e8\u8fdb\u884c\u7f29\u653e\uff0c\u65e0\u9700\u4e8b\u5148\u7f29\u653e\u6570\u636e\u3002<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code><code><em> define the size of the test set<\/em><\/code><code>test_size = int(0.3 * len(dataset))<\/code><code><em># extract the training data<\/em><\/code><code>training_dataset = dataset.iloc&#91;:- test_size - context_length - prediction_length - 1]<\/code><code><em># extract the test data<\/em><\/code><code>test_dataset = dataset.iloc&#91;- test_size - context_length - prediction_length - 1:]<\/code><\/code><\/pre>\n\n\n\n<p>\u73b0\u5728\u5c06\u8bad\u7ec3\u6570\u636e\u4fdd\u5b58\u81f3 S3 \u4e2d\uff0c\u6784\u5efa SageMaker \u4f30\u7b97\u5668\u5e76\u8fd0\u884c\u8bad\u7ec3\u4f5c\u4e1a\u3002<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code><code># upload the training data to S3<\/code><code>training_data = sagemaker_session.upload_string_as_file_body(<\/code><code>    body=training_dataset.to_csv(index=False),<\/code><code>    bucket=bucket,<\/code><code>    key=\"training_data.csv\"<\/code><code>)<\/code><code><br><\/code><code># create the estimator<\/code><code>estimator = sagemaker.algorithm.AlgorithmEstimator(<\/code><code>    algorithm_arn=algo_arn,<\/code><code>    role=role,<\/code><code>    instance_count=1,<\/code><code>    instance_type=instance_type,<\/code><code>    input_mode=\"File\",<\/code><code>    sagemaker_session=sagemaker_session,<\/code><code>    hyperparameters=hyperparameters<\/code><code>)<\/code><code><br><\/code><code># run the training job<\/code><code>estimator.fit({\"training\": training_data})<\/code><\/code><\/pre>\n\n\n\n<p>\u8bad\u7ec3\u4f5c\u4e1a\u5b8c\u6210\u540e\uff0c\u6211\u4eec\u5c06\u6a21\u578b\u90e8\u7f72\u81f3\u53ef\u7528\u4e8e\u63a8\u7406\u7684\u5b9e\u65f6\u7aef\u70b9\u3002<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>\nserializer = sagemaker.serializers.CSVSerializer(content_type=\"text\/csv\")\n\ndeserializer = sagemaker.base_deserializers.PandasDeserializer(accept=\"text\/csv\")\n\npredictor = estimator.deploy(\n    initial_instance_count=1,\n    instance_type=instance_type,)<\/code><\/pre>\n\n\n\n<p>\u521b\u5efa\u7aef\u70b9\u540e\uff0c\u6211\u4eec\u80fd\u591f\u751f\u6210\u6d4b\u8bd5\u96c6\u9884\u6d4b\u3002\u9274\u4e8e\u6211\u4eec\u8fd0\u7528\u6eda\u52a8\uff08\u6216\u91cd\u53e0\uff09\u56de\u62a5\uff0c\u6211\u4eec\u4ec5\u5bf9\u6bcf\u4e2a\u9884\u6d4b\u5e8f\u5217\u7684\u6700\u540e\u4e00\u4e2a\u5143\u7d20\u611f\u5174\u8da3\uff08\u56de\u60f3\u4e00\u4e0b\uff0c\u6211\u4eec\u5c06\u9884\u6d4b\u957f\u5ea6\u8bbe\u5b9a\u4e3a 30 \u5929\uff0c\u4e0e\u56de\u62a5\u7684\u8303\u56f4\u76f8\u540c\uff09\u3002<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code><code># create a list for storing the predictions<\/code><code>predictions = &#91;]<\/code><code><br><\/code><code># loop across the dates<\/code><code>for t in range(context_length, len(test_dataset) - prediction_length + 1):<\/code><code><br><\/code><code>    # extract the inputs<\/code><code>    payload = test_dataset.iloc&#91;t - context_length: t]<\/code><code><br><\/code><code>    # invoke the endpoint<\/code><code>    response = sagemaker_session.sagemaker_runtime_client.invoke_endpoint(<\/code><code>        EndpointName=predictor.endpoint_name,<\/code><code>        ContentType=\"text\/csv\",<\/code><code>        Body=payload.to_csv(index=False)<\/code><code>    )<\/code><code><br><\/code><code>    # deserialize the endpoint response<\/code><code>    response = deserializer.deserialize(response&#91;\"Body\"], content_type=\"text\/csv\")<\/code><code><br><\/code><code>    # extract the predicted 30-day return<\/code><code>    prediction = response.iloc&#91;-1:]<\/code><code><br><\/code><code>    # extract the date corresponding to the predicted 30-day return<\/code><code>    prediction.index = &#91;test_dataset.index&#91;t + prediction_length - 1]]<\/code><code><br><\/code><code>    # save the prediction<\/code><code>    predictions.append(prediction)<\/code><code><br><\/code><code># cast the predictions to data frame<\/code><code>predictions = pd.concat(predictions)<\/code><code><br><\/code><code># add the actual values<\/code><code>predictions&#91;\"y\"] = test_dataset&#91;\"y\"]<\/code><\/code><\/pre>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img decoding=\"async\" src=\"http:\/\/123.60.176.65\/wp-content\/uploads\/2024\/07\/640-1-1.webp\" alt=\"\" class=\"wp-image-625\"\/><\/figure>\n<\/div>\n\n\n<p>\u6d4b\u8bd5\u96c6\uff08\u4ece 2023-12-04 \u81f3 2024-06-28\uff09\u7684\u5b9e\u9645\u548c\u9884\u6d4b 30 \u5929\u56de\u62a5\u7387\u3002<\/p>\n\n\n\n<p>\u6211\u4eec\u8fd0\u7528\u4ee5\u4e0b\u6307\u6807\u8bc4\u4f30\u6d4b\u8bd5\u96c6\u9884\u6d4b\uff1a<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>RMSE\uff1a\u8fd4\u56de\u503c\u9884\u6d4b\u503c\u7684\u5747\u65b9\u6839\u8bef\u5dee\u3002<\/li>\n\n\n\n<li>MAE\uff1a\u8fd4\u56de\u9884\u6d4b\u503c\u7684\u5e73\u5747\u7edd\u5bf9\u8bef\u5dee\u3002<\/li>\n\n\n\n<li>\u51c6\u786e\u6027\uff1a\u9884\u6d4b\u56de\u62a5\u8ff9\u8c61\u7684\u51c6\u786e\u6027\u3002<\/li>\n\n\n\n<li>F1\uff1a\u9884\u6d4b\u56de\u62a5\u8ff9\u8c61\u7684 F1 \u5206\u6570\u3002<\/li>\n<\/ul>\n\n\n\n<pre class=\"wp-block-code\"><code><code># calculate the model performance metrics<\/code><code>metrics = pd.DataFrame(<\/code><code>    columns=&#91;\"Metric\", \"Value\"],<\/code><code>    data=&#91;<\/code><code>        {\"Metric\": \"RMSE\", \"Value\": root_mean_squared_error(y_true=predictions&#91;\"y\"], y_pred=predictions&#91;\"y_mean\"])},<\/code><code>        {\"Metric\": \"MAE\", \"Value\": mean_absolute_error(y_true=predictions&#91;\"y\"], y_pred=predictions&#91;\"y_mean\"])},<\/code><code>        {\"Metric\": \"Accuracy\", \"Value\": accuracy_score(y_true=predictions&#91;\"y\"] &gt; 0, y_pred=predictions&#91;\"y_mean\"] &gt; 0)},<\/code><code>        {\"Metric\": \"F1\", \"Value\": f1_score(y_true=predictions&#91;\"y\"] &gt; 0, y_pred=predictions&#91;\"y_mean\"] &gt; 0)},<\/code><code>    ]<\/code><code>)<\/code><\/code><\/pre>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img decoding=\"async\" src=\"http:\/\/123.60.176.65\/wp-content\/uploads\/2024\/07\/640-2-1.webp\" alt=\"\" class=\"wp-image-627\"\/><\/figure>\n<\/div>\n\n\n<p>\u6d4b\u8bd5\u96c6\uff08\u4ece 2023-12-04 \u81f3 2024-06-28\uff09\u9884\u6d4b\u7684 30 \u5929\u56de\u62a5\u7684\u6027\u80fd\u6307\u6807\u3002<\/p>\n\n\n\n<p>\u73b0\u5728\u6211\u4eec\u80fd\u591f\u5220\u9664\u6a21\u578b\u4e0e\u7aef\u70b9\u3002<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><\/li>\n<\/ul>\n\n\n\n<pre class=\"wp-block-code\"><code><code>predictor.delete_model()<\/code><code>predictor.delete_endpoint(delete_endpoint_config=True)<\/code><\/code><\/pre>\n\n\n\n<p><strong>6.\u9884\u6d4b<\/strong><\/p>\n\n\n\n<p>\u6211\u4eec\u8fd0\u7528\u6240\u6709\u53ef\u7528\u6570\u636e\u91cd\u65b0\u8bad\u7ec3\u6a21\u578b\uff0c\u5e76\u751f\u6210\u6837\u672c\u5916\u9884\u6d4b\uff0c\u4e5f\u5c31\u662f\u8bf4\uff0c\u6211\u4eec\u9884\u6d4b\u5f53\u524d\u65e5\u671f\uff082024-06-28\uff09\u4e4b\u540e 30\uff08\u5de5\u4f5c\u65e5\uff09\u7684 30 \u5929\u56de\u62a5\u3002<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>data = sagemaker_session.upload_string_as_file_body(<br>body=dataset.to_csv(index=False),<br>bucket=bucket,<br>key=\"dataset.csv\"<br>)<br>estimator = sagemaker.algorithm.AlgorithmEstimator(<br>algorithm_arn=algo_arn,<br>role=role,<br>instance_count=1,<br>instance_type=instance_type,<br>input_mode=\"File\",<br>sagemaker_session=sagemaker_session,<br>hyperparameters=hyperparameters<br>)<br>estimator.fit({\"training\": data})<\/code><\/pre>\n\n\n\n<p>\u9274\u4e8e\u6211\u4eec\u4ec5\u9700\u8981\u4e00\u4e2a\u9884\u6d4b\u7684 30 \u5929\u5e8f\u5217\uff0c\u6211\u4eec\u8fd0\u7528\u6279\u91cf\u53d8\u6362\u4ee5\u751f\u6210\u9884\u6d4b\u3002<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>inputs = sagemaker_session.upload_string_as_file_body(<br>body=dataset.iloc&#91;- context_length:].to_csv(index=False),<br>bucket=bucket,<br>key=\"inputs.csv\"<br>)<br>transformer = estimator.transformer(<br>instance_count=1,<br>instance_type=instance_type,<br>)<br>transformer.transform(<br>data=inputs,<br>content_type=\"text\/csv\",<br>)<\/code><\/pre>\n\n\n\n<p>\u6279\u91cf\u8f6c\u6362\u4f5c\u4e1a\u5b8c\u6210\u540e\uff0c\u6211\u4eec\u80fd\u591f\u4ece S3 \u52a0\u8f7d\u9884\u6d4b\u3002<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code><code>forecasts = sagemaker_session.read_s3_file(<\/code><code>    bucket=bucket,<\/code><code>    key_prefix=f\"{transformer.latest_transform_job.name}\/inputs.csv.out\"<\/code><code>)<\/code><code><br><\/code><code>forecasts = pd.read_csv(io.StringIO(forecasts), dtype=float).dropna()<\/code><code><br><\/code><code>forecasts.index = pd.date_range(<\/code><code>    start=dataset.index&#91;-1] + pd.Timedelta(days=1),<\/code><code>    periods=prediction_length,<\/code><code>    freq=\"B\"<\/code><code>)<\/code><\/code><\/pre>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img decoding=\"async\" src=\"http:\/\/123.60.176.65\/wp-content\/uploads\/2024\/07\/640-3-1.webp\" alt=\"\" class=\"wp-image-629\"\/><\/figure>\n<\/div>\n\n\n<p>30 \u5929\u6837\u672c\u5916\u9884\u6d4b\u56de\u62a5\uff08\u4ece 2024-07-01 \u81f3 2024-08-09\uff09\u3002<\/p>\n\n\n\n<p>\u8fd9\u4e2a\u9884\u6d4b\u80a1\u7968\u56de\u62a5\u7684\u6d4b\u8bd5\u5230\u8fd9\u91cc\u5c31\u7ed3\u675f\u4e86\uff0c\u6700\u540e\u671f\u671b\u5173\u6ce8\u6211\u7684\u670b\u53cb\u4eec\u65e9\u65e5\u5b9e\u73b0\u8d22\u5bcc\u81ea\u7531\uff01<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"has-text-align-center has-cyan-bluish-gray-color has-text-color has-link-color wp-elements-bd402b7c146898dcf3d05749282e5860\"><strong>\u672c\u6587\u5185\u5bb9\u4ec5\u4ec5\u662f\u6280\u672f\u63a2\u8ba8\u548c\u5b66\u4e60\uff0c\u5e76\u4e0d\u6784\u6210\u4efb\u4f55\u6295\u8d44\u5efa\u8bae\u3002<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u5199\u5728\u524d\u9762\u7684\u8bdd\uff1a\u5b66\u672f\u7814\u7a76\u8005\u4e0e\u884c\u4e1a\u4ece\u4e1a\u8005\u59cb\u7ec8\u9488\u5bf9\u80a1\u7968\u56de&#8230;<\/p>\n<div class=\"more-link-wrapper\"><a class=\"more-link\" href=\"https:\/\/laoyulaoyu.com\/index.php\/2024\/07\/11\/%e6%89%8b%e6%8a%8a%e6%89%8b%e6%95%99%e4%bd%a0ai%e9%a1%be%e6%8a%95%ef%bc%9aai%e5%af%b9%e8%82%a1%e7%a5%a8%e5%9b%9e%e6%8a%a5%e7%9a%84%e7%b2%be%e5%87%86%e9%a2%84%e6%b5%8b%ef%bc%88%e8%bf%90%e7%94%a8-cfc-sa\/\">Continue reading<span class=\"screen-reader-text\">\u624b\u628a\u624b\u6559\u4f60ai\u987e\u6295\uff1aAI\u5bf9\u80a1\u7968\u56de\u62a5\u7684\u7cbe\u51c6\u9884\u6d4b\uff08\u8fd0\u7528 CFC SageMaker \u7b97\u6cd5\u7684 LNN\uff09<\/span><\/a><\/div>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[5],"class_list":["post-621","post","type-post","status-publish","format-standard","hentry","category-aiinvest","tag-ai","entry"],"_links":{"self":[{"href":"https:\/\/laoyulaoyu.com\/index.php\/wp-json\/wp\/v2\/posts\/621","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/laoyulaoyu.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/laoyulaoyu.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/laoyulaoyu.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/laoyulaoyu.com\/index.php\/wp-json\/wp\/v2\/comments?post=621"}],"version-history":[{"count":0,"href":"https:\/\/laoyulaoyu.com\/index.php\/wp-json\/wp\/v2\/posts\/621\/revisions"}],"wp:attachment":[{"href":"https:\/\/laoyulaoyu.com\/index.php\/wp-json\/wp\/v2\/media?parent=621"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/laoyulaoyu.com\/index.php\/wp-json\/wp\/v2\/categories?post=621"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/laoyulaoyu.com\/index.php\/wp-json\/wp\/v2\/tags?post=621"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}