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Python机器学习_预测分析核心算法_all code

于 2018-05-08 发布 文件大小:158KB
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下载积分: 1 下载次数: 11

代码说明:

  Python机器学习——预测分析核心算法(MICHAEL BOWLES teaches machine learning at Hacker Dojo in Silicon Valley, consults on machine learning projects, and is involved in a number of startups in such areas as bioinformatics and high-frequency trading. Following an assistant professorship at MIT, Michael went on to found and run two Silicon Valley startups, both of which went public. His courses at Hacker Dojo are nearly always sold out and receive great feedback from participants.)

文件列表:

06\chapter06.zip, 12602 , 2015-02-26
06\simpleBagging.py, 2973 , 2015-02-26
06\simpleGBM.py, 3093 , 2015-02-26
06\simpleTree.py, 3087 , 2015-02-26
06\simpleTreeCV.py, 2076 , 2015-02-26
06\wineBagging.py, 3213 , 2015-02-26
06\wineGBM.py, 3086 , 2015-02-26
06\wineRF.py, 3788 , 2015-02-26
06\wineTree.py, 1327 , 2015-02-26
07\abaloneGBM.py, 3466 , 2015-02-26
07\abaloneRF.py, 2979 , 2015-02-26
07\glassGbm.py, 5773 , 2015-02-26
07\glassRF.py, 4315 , 2015-02-26
07\rocksVMinesGBM.py, 6168 , 2015-02-26
07\rocksVMinesRF.py, 4856 , 2015-02-26
07\timingComparisons.txt, 762 , 2015-02-26
07\wineBagging.py, 3281 , 2015-02-26
07\wineGBM.py, 2838 , 2015-02-26
07\wineRF.py, 2503 , 2015-02-26
01\chapter01.txt, 73 , 2015-02-26
02\abaloneCorrHeat.py, 684 , 2015-02-26
02\abaloneCorrMat.txt, 1136 , 2015-02-26
02\abaloneParallelPlot.py, 1481 , 2015-02-26
02\abaloneSummary.py, 1679 , 2015-02-26
02\abaloneSummaryOutput.txt, 2325 , 2015-02-26
02\chapter02.zip, 24592 , 2015-02-26
02\corrCalc.py, 1617 , 2015-02-26
02\corrPlot.py, 769 , 2015-02-26
02\glassCorrHeatMap.py, 620 , 2015-02-26
02\glassParallelPlot.py, 1174 , 2015-02-26
02\glassSummary.py, 984 , 2015-02-26
02\glassSummary.txt, 1672 , 2015-02-26
02\linePlots.py, 768 , 2015-02-26
02\outputRocksVMinesContents.txt, 624 , 2015-02-26
02\outputSummaryStats.txt, 526 , 2015-02-26
02\pandasReadSummarize.py, 538 , 2015-02-26
02\pandasReadSummarizeOutput.txt, 1431 , 2015-02-26
02\qqplotAttribute.py, 756 , 2015-02-26
02\rockVmineContents.py, 1181 , 2015-02-26
02\rockVmineSummaries.py, 608 , 2015-02-26
02\rVMSummaryStats.py, 1952 , 2015-02-26
02\sampleCorrHeatMap.py, 541 , 2015-02-26
02\targetCorr.py, 1435 , 2015-02-26
02\wineCorrHeatMap.py, 503 , 2015-02-26
02\wineParallelPlot.py, 1854 , 2015-02-26
02\wineSummary.py, 782 , 2015-02-26
02\wineSummary.txt, 2780 , 2015-02-26
03\chapter03.zip, 8123 , 2015-02-26
03\classifierPerformance_RocksVMines.py, 4714 , 2015-02-26
03\classifierPerformance_RocksVMinesOutput.txt, 494 , 2015-02-26
03\classifierRidgeRocksVMines.py, 2424 , 2015-02-26
03\classifierRidgeRocksVMinesOutput.txt, 375 , 2015-02-26
03\fwdStepwiseWine.py, 4184 , 2015-02-26
03\fwdStepwiseWineOutput.txt, 562 , 2015-02-26
03\regressionErrorMeasures.py, 1794 , 2015-02-26
03\ridgeWine.py, 2569 , 2015-02-26
03\ridgeWineOutput.txt, 317 , 2015-02-26
04\chapter04.zip, 14423 , 2015-02-26
04\cvCurveDetails.txt, 105 , 2015-02-26
04\glmnetOrderedNamesList.txt, 120 , 2015-02-26
04\glmnetWine.py, 4706 , 2015-02-26
04\larsAbalone.py, 3493 , 2015-02-26
04\larsAbaloneOutput.txt, 74 , 2015-02-26
04\larsRocksVMines.py, 3280 , 2015-02-26
04\larsWine.py, 1904 , 2015-02-26
04\larsWine2.py, 3185 , 2015-02-26
04\larsWineCV.py, 4335 , 2015-02-26
04\orderedNamesList.txt, 195 , 2015-02-26
04\rocksVMinesCoefOrder.txt, 163 , 2015-02-26
04\wineBasisExpand.py, 1379 , 2015-02-26
05\chapter05.zip, 25049 , 2015-02-26
05\glass, 0 , 2015-02-27
05\glass\glassENetRegCV.py, 4318 , 2015-02-26
05\rocksVMines, 0 , 2015-02-27
05\rocksVMines\rocksVMinesCoefCurves.py, 3676 , 2015-02-26
05\rocksVMines\rocksVMinesCoefCurvesPrintedOutput.txt, 1777 , 2015-02-26
05\rocksVMines\rocksVMinesENetRegCV.py, 6301 , 2015-02-26
05\rocksVMines\rocksVMinesENetRegCVPrintedOutput.txt, 655 , 2015-02-26
05\rocksVMines\rocksVMinesGlmnet.py, 7162 , 2015-02-26
05\rocksVMines\rocksVMinesGlmnetPrintedOutput.txt, 468 , 2015-02-26
05\wineCS, 0 , 2015-02-27
05\wineCS\wineExpandedLassoCV.py, 3201 , 2015-02-26
05\wineCS\wineLassoCoefCurves.py, 3638 , 2015-02-26
05\wineCS\wineLassoCoefCurvesPrintedOutput.txt, 1236 , 2015-02-26
05\wineCS\wineLassoCV.py, 2867 , 2015-02-26
05\wineCS\wineLassoCVPrintedOutputNormalizedX.txt, 103 , 2015-02-26
05\wineCS\wineLassoCVPrintedOutputNormalizedXandY.txt, 105 , 2015-02-26
05\wineCS\wineLassoCVPrintedOutputUn-NormalizedX.txt, 106 , 2015-02-26
05\wineCS\wineLassoExpandedCVPrintedOutput.txt, 105 , 2015-02-26
新建文本文档.txt, 440 , 2018-05-08

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发表评论

0 个回复

  • 75642532
    winsock完成端口,易语言写的网络相关程序,很好的参考。(The Winsock completion port, easy to network related written procedures, a good reference.)
    2013-10-01 14:10:32下载
    积分:1
  • 244289
    网络下载例程程序,结合易语言网络传送支持库和易语言扩展界面支持库,实现进度多线程下载。(Download routine program , combined with easy language support library network transmission interface and ease of language extensions to support library that implements multi-threaded download progress .)
    2016-04-02 09:09:01下载
    积分:1
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    说明:  网络编程之异步IO之Select模型源码!!!!(WinSock Select code good good good good good!)
    2019-04-02 16:48:55下载
    积分:1
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    openlayers必须的openlayer文件(Gis have to get a ol.js)
    2020-06-16 21:20:02下载
    积分:1
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    简化Sock连接。采用队列保存Sock的收发消息包,保证消息的处理顺序。(Simplify the Sock connection)
    2012-05-28 11:19:06下载
    积分:1
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    C++文件传输(有客户端服务器),C++ socket 编程实现,支持断点续传,可供参考学习用。  没有做太多的测试,如果有错误欢迎指正。
    2022-05-25 18:38:24下载
    积分:1
  • LanTalk_sources
    Currently, most of people use MS DCOM/COM+, Java Bean/RMI, and Corba to do distributed computing over internet. All of these technologies are provided with some tools and intermediate objects to simplify internet development. However, these technologies have one common and fundamental problem that all of the calls between a client and a server are blocked for a returned result (please correct me if this is wrong). A client stays still, and has to wait for a while after sending a request to a server. If the request is a lengthy action, the client application seems to be dead to a user. In most cases, we could use a worker thread at the client side to do background computation for solving this problem. However, this comes with an expensive price, more coding, data synchronization and mess in coding logic. Additionally, I also doubt that these technologies are able to really move data across internet efficiently.
    2009-06-27 15:00:43下载
    积分:1
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    该项目涉及通过特定网络连接的各种终端系统的功能。这提高了管理员的工作效率,还可以减少物理工作应变而不仅仅是对用户而且对管理员。它还可以用于减少不必要的功耗在一个组织中。 其协作体系结构带来了严重的安全挑战。这些协作解决方案之一是提供了一个虚拟的图形环境,通过网络在瘦客户端上显示远程桌面。当几个瘦客户机访问到相同的主机,可以提高冲突或任何类型的干涉问题。这个行政的远程控制设置远程连接使用 RDP (远程桌面协议)。 远程桌面协议 (RDP) 有无集中化的管理、 有限的身份管理集成、 没有审计或报告,和没有协作功能。 RDP 是为局域网 (LAN) 上的远程访问设计的。建立远程桌面连接到远程网络上的计算机通常需要妥协安全 — — 比如说打开默认侦听端口,VPN 隧道和防火墙配置 TCP 3389。
    2022-12-10 22:40:03下载
    积分:1
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    2021-01-19 15:28:42下载
    积分:1
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