{"id":73,"date":"2016-08-12T15:14:41","date_gmt":"2016-08-12T07:14:41","guid":{"rendered":"http:\/\/ayonel.me\/?p=73"},"modified":"2016-08-25T01:47:20","modified_gmt":"2016-08-24T17:47:20","slug":"weka_naivebayes","status":"publish","type":"post","link":"https:\/\/ayonel.malash.net\/index.php\/2016\/08\/12\/weka_naivebayes\/","title":{"rendered":"\u7528weka\u8fdb\u884c\u591a\u9879\u5f0f\u6734\u7d20\u8d1d\u53f6\u65af\u589e\u91cf\u5b66\u4e60"},"content":{"rendered":"

\u6709\u65f6\u5019\u6211\u4eec\u8fdb\u884c\u8d1d\u53f6\u65af\u5206\u7c7b\u65f6\uff0c\u7531\u4e8e\u6570\u636e\u91cf\u592a\u5927\u5bfc\u81f4\u5185\u5b58\u6ea2\u51fa\u6216\u8005\u5bf9\u6a21\u578b\u7684\u8bad\u7ec3\u6709\u7740\u7279\u6b8a\u8981\u6c42(\u6bd4\u5982\u7528\u7b2c\u4e00\u4e2a\u6708\u7684\u6570\u636e\u9884\u6d4b\u7b2c\u4e8c\u4e2a\u6708\uff0c\u518d\u5c06\u7b2c\u4e8c\u4e2a\u6708\u7684\u6570\u636e\u52a0\u5165\u5df2\u7ecf\u8bad\u7ec3\u597d\u7684\u6a21\u578b\uff0c\u53bb\u9884\u6d4b\u7b2c\u4e09\u4e2a\u6708…)\uff0c\u8fd9\u65f6\u666e\u901a\u7684\u8d1d\u53f6\u65af\u5206\u7c7b\u4e0d\u884c\u4e86\u3002\u6211\u4eec\u9700\u8981\u4f7f\u7528\u8d1d\u53f6\u65af\u6765\u8fdb\u884c\u589e\u91cf\u5b66\u4e60\uff08incremental learning\uff09, weka\u7684\u8d1d\u53f6\u65af\u5206\u7c7b\u5668\u5373\u5b58\u5728\u589e\u91cf\u5f0f\u7684\u8d1d\u53f6\u65af\u5206\u7c7b\u5668\u3002\u4e0b\u6587\u4ee5\u591a\u9879\u5f0f\u6734\u7d20\u8d1d\u53f6\u65af\u589e\u91cf\u5b66\u4e60\u4e3a\u4f8b\uff0cweka\u4e2d\u7684\u5305\u4e3a\uff1a<\/p>\n

weka.classifiers<\/span>.bayes<\/span>.NaiveBayesMultinomialUpdateable<\/span><\/div><\/div>\n

\u4e0b\u6587\u662f\u6838\u5fc3\u4ee3\u7801\uff1a<\/p>\n

        \/\/\u83b7\u53d6\u7b2c\u4e00\u4e2a\u6708\u7684\u6570\u636e\u7528\u4e8e\u5efa\u7acb\u6a21\u578b<\/span>
\n        ArffLoader loader =<\/span> new<\/span> ArffLoader(<\/span>)<\/span>;<\/span>
\n        loader.setFile<\/span>(<\/span>new<\/span> File<\/span>(<\/span>"month1.arff"<\/span>)<\/span>)<\/span>;<\/span>
\n        loader.getStructure<\/span>(<\/span>)<\/span>;<\/span>\/\/\u8fd9\u53e5\u8bdd\u5fc5\u987b\u6709\uff0c\u4e0d\u7136\u4f1a\u62a5\u9519<\/span>
\n
\n        \/\/\u5b9a\u4e49\u5206\u7c7b\u5668 \u5e76\u7528\u7b2c\u4e00\u4e2a\u6708\u7684\u6570\u636e\u505a\u8bad\u7ec3<\/span>
\n        Instances originDataSet =<\/span> loader.getDataSet<\/span>(<\/span>)<\/span>;<\/span>\/\/\u83b7\u53d6\u7b2c\u4e00\u4e2a\u6708\u7684\u5b9e\u4f8b<\/span>
\n        originDataSet.setClassIndex<\/span>(<\/span>originDataSet.numAttributes<\/span>(<\/span>)<\/span>-<\/span>1<\/span>)<\/span>;<\/span>\/\/\u5b9a\u4e49\u6700\u540e\u4e00\u4e2a\u5c5e\u6027\u4f5c\u4e3a\u5206\u7c7b\u76ee\u6807<\/span>
\n        NaiveBayesMultinomialUpdateable nb =<\/span> new<\/span> NaiveBayesMultinomialUpdateable(<\/span>)<\/span>;<\/span>\/\/\u5b9a\u4e49\u6a21\u578b<\/span>
\n        nb.buildClassifier<\/span>(<\/span>originDataSet)<\/span>;<\/span>\/\/\u5efa\u7acb\u6a21\u578b<\/span>
\n
\n        \/\/\u5bf9\u4ece\u7b2c\u4e8c\u4e2a\u6708\u8d77\u7684\u6bcf\u4e2a\u6708\u8fdb\u884c\u9884\u6d4b\u548c\u8bad\u7ec3,\u4e00\u76f4\u5230\u7b2c100\u4e2a\u6708,(2,100\u53ea\u662f\u7528\u4e8e\u793a\u4f8b)<\/span>
\n        for<\/span> (<\/span>int<\/span> month =<\/span> 2<\/span>;<\/span> month <=<\/span> 100<\/span>;<\/span> month++<\/span>)<\/span> {<\/span>
\n            \/\/\u8bfb\u53d6\u6d4b\u8bd5\u96c6<\/span>
\n            ArffLoader testLoader =<\/span> new<\/span> ArffLoader(<\/span>)<\/span>;<\/span>
\n            testLoader.setFile<\/span>(<\/span>new<\/span> File<\/span>(<\/span>"month"<\/span>+<\/span>i+<\/span>".arff"<\/span>)<\/span>)<\/span>;<\/span>
\n            testLoader.getStructure<\/span>(<\/span>)<\/span>;<\/span>
\n
\n            Instances testDataSet =<\/span> testLoader.getDataSet<\/span>(<\/span>)<\/span>;<\/span>\/\/\u83b7\u53d6\u6d4b\u8bd5\u96c6\u5b9e\u4f8b<\/span>
\n            \/\/\u8fdb\u884c\u5206\u7c7b\uff0c\u5e76\u4e14\u8f93\u51fa<\/span>
\n            for<\/span> (<\/span>int<\/span> i =<\/span> 0<\/span>;<\/span> i<<\/span> testDataSet.numInstances<\/span>(<\/span>)<\/span>;<\/span> i++<\/span>)<\/span> {<\/span>
\n                FileWriter<\/span> fileWritter =<\/span> new<\/span> FileWriter<\/span>(<\/span>"output.txt"<\/span>, true<\/span>)<\/span>;<\/span>
\n                BufferedWriter<\/span> bufferWritter =<\/span> new<\/span> BufferedWriter<\/span>(<\/span>fileWritter)<\/span>;<\/span>
\n                bufferWritter.write<\/span>(<\/span>nb.distributionForInstance<\/span>(<\/span>testDataSet.instance<\/span>(<\/span>i)<\/span>)<\/span>[<\/span>1<\/span>]<\/span>+<\/span>'\\n<\/span>'<\/span>)<\/span>;<\/span>\/\/\u8fd9\u4e00\u884c\u8f93\u51fa\u7684\u662f\u5206\u7c7b\u4e2d\u5206\u5230\u7b2c\u4e8c\u7c7b(\u4e0b\u6807\u4e3a1)\u7684\u6982\u7387<\/span>
\n                bufferWritter.flush<\/span>(<\/span>)<\/span>;<\/span>
\n            }<\/span>
\n
\n            \/\/ \u518d\u628a\u8fd9\u6b21\u7684\u6d4b\u8bd5\u96c6\u5f53\u505a\u8bad\u7ec3\u96c6\u8fdb\u884c\u8bad\u7ec3<\/span>
\n            for<\/span> (<\/span>int<\/span> i =<\/span> 0<\/span>;<\/span> i<<\/span> testDataSet.size<\/span>(<\/span>)<\/span>;<\/span> i++<\/span>)<\/span> {<\/span>
\n                testDataSet.setClassIndex<\/span>(<\/span>testDataSet.numAttributes<\/span>(<\/span>)<\/span>-<\/span>1<\/span>)<\/span>;<\/span>
\n                nb.updateClassifier<\/span>(<\/span>testDataSet.get<\/span>(<\/span>i)<\/span>)<\/span>;<\/span>
\n            }<\/span><\/div><\/div>\n","protected":false},"excerpt":{"rendered":"

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