\u3053\u306e\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3067\u306f\u3001\u3044\u304f\u3064\u304b\u306e\u57fa\u672c\u7684\u306aJava\u30d1\u30c3\u30b1\u30fc\u30b8\u304c\u5fc5\u8981\u3067\u3059\u3002<\/p>\n
\n
\nimport java.util.Properties;\nimport java.util.Scanner;\nimport java.io.File;\nimport java.io.Reader;\nimport java.io.StringReader;<\/code><\/pre>\n<\/div>\nGridDB\u306b\u63a5\u7d9a\u3057\u64cd\u4f5c\u3092\u884c\u3046\u306b\u306f\u3001\u4ee5\u4e0b\u306e\u30d1\u30c3\u30b1\u30fc\u30b8\u3092\u542b\u3081\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n
\n
\nimport com.toshiba.mwcloud.gs.Collection;\nimport com.toshiba.mwcloud.gs.GSException;\nimport com.toshiba.mwcloud.gs.GridStore;\nimport com.toshiba.mwcloud.gs.GridStoreFactory;\nimport com.toshiba.mwcloud.gs.Query;\nimport com.toshiba.mwcloud.gs.RowKey;\nimport com.toshiba.mwcloud.gs.RowSet;<\/code><\/pre>\n<\/div>\n\u30c7\u30fc\u30bf\u5206\u6790\u306b\u306f\u3001Weka\u306e\u4ee5\u4e0b\u306e\u30d1\u30c3\u30b1\u30fc\u30b8\u3092\u542b\u3081\u307e\u3059\u3002<\/p>\n
\n
\nimport weka.classifiers.Evaluation;\nimport weka.classifiers.functions.LinearRegression;\nimport weka.core.Instances;\nimport weka.filters.Filter;\nimport weka.filters.unsupervised.attribute.Normalize;<\/code><\/pre>\n<\/div>\nW\u3055\u3066\u3001\u3053\u308c\u304c\u6700\u521d\u306e\u30b9\u30c6\u30c3\u30d7\u3067\u3059\u3002<\/p>\n
\u6b21\u306e\u30b9\u30c6\u30c3\u30d7\u306b\u9032\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n
\u30c7\u30fc\u30bf\u3092\u683c\u7d0d\u3059\u308b\u305f\u3081\u306e\u30af\u30e9\u30b9\u306e\u4f5c\u6210<\/h2>\n
\u3053\u306e\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3067\u306f\u3001GridDB\u30b3\u30f3\u30c6\u30ca\u306b\u30c7\u30fc\u30bf\u3092\u683c\u7d0d\u3057\u307e\u3059\u3002\u305d\u306e\u305f\u3081\u3001\u30b3\u30f3\u30c6\u30ca\u306e\u30b9\u30ad\u30fc\u30de\u3092\u9759\u7684\u30af\u30e9\u30b9\u3068\u3057\u3066\u5b9a\u7fa9\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n
\n
\nstatic class House {\n @RowKey int housesize;\n int lotsize;\n int bedrooms;\n int granite;\n int bathroom;\n int sellingprice;\n}<\/code><\/pre>\n<\/div>\n\u9759\u7684\u30af\u30e9\u30b9 House<\/code> \u306f\u3001RowKey<\/code> housesize<\/code> \u3092\u6301\u30646\u3064\u306e\u6574\u6570\u578b\u30ab\u30e9\u30e0\u3067\u69cb\u6210\u3055\u308c\u307e\u3059\u3002<\/p>\nGridDB \u63a5\u7d9a\u306e\u4f5c\u6210<\/h2>\n
\u30b9\u30ad\u30fc\u30de\u30af\u30e9\u30b9\u306f\u6e96\u5099\u3067\u304d\u307e\u3057\u305f\u3002GridDB\u306b\u63a5\u7d9a\u3059\u308b\u6642\u304c\u6765\u307e\u3057\u305f\u3002<\/p>\n
GridDB\u63a5\u7d9a\u3092\u4f5c\u6210\u3059\u308b\u306b\u306f\u3001GridDB\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u306e\u8a8d\u8a3c\u60c5\u5831\u3092\u5b9a\u7fa9\u3059\u308bProperties<\/code>\u30a4\u30f3\u30b9\u30bf\u30f3\u30b9\u3092\u521d\u671f\u5316\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u6b21\u306e\u30b3\u30fc\u30c9\u3092\u898b\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n\n
\nProperties props = new Properties();\nprops.setProperty(\"notificationMember\", \"127.0.0.1:10001\");\nprops.setProperty(\"clusterName\", \"myCluster\");\nprops.setProperty(\"user\", \"admin\");\nprops.setProperty(\"password\", \"admin\");\nGridStore store = GridStoreFactory.getInstance().getGridStore(props);<\/code><\/pre>\n<\/div>\nGridDB\u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u72b6\u6cc1\u306b\u5fdc\u3058\u3066\u3001\u3053\u308c\u3089\u306e\u63a5\u7d9a\u60c5\u5831\u3092\u5909\u66f4\u3059\u308b\u5fc5\u8981\u304c\u3042\u308b\u304b\u3082\u3057\u308c\u307e\u305b\u3093\u3002<\/p>\n
\u63a5\u7d9a\u306b\u6210\u529f\u3057\u305f\u3089\u3001\u6b21\u306b\u30b3\u30ec\u30af\u30b7\u30e7\u30f3\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002<\/p>\n
\n
\nCollection coll = store.putCollection(\"House\", House.class);<\/code><\/pre>\n<\/div>\n\u3053\u3053\u3067\u306f\u3001\u30b3\u30f3\u30c6\u30ca House<\/code> \u306e\u30b3\u30ec\u30af\u30b7\u30e7\u30f3\u30aa\u30d6\u30b8\u30a7\u30af\u30c8 coll<\/code> \u3092\u4f5c\u6210\u3057\u307e\u3057\u305f\u3002<\/p>\nGridDB\u306b\u30c7\u30fc\u30bf\u3092\u30d7\u30c3\u30b7\u30e5<\/h2>\n
\u3053\u308c\u3067GridDB\u306e\u30b9\u30ad\u30fc\u30de\u304c\u5b8c\u6210\u3057\u3001\u63a5\u7d9a\u306e\u6e96\u5099\u304c\u6574\u3044\u307e\u3057\u305f\u3002<\/p>\n
\u305d\u308c\u3067\u306f\u3001\u3044\u304f\u3064\u304b\u306e\u30c7\u30fc\u30bf\u3092\u5165\u308c\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n
\u3053\u306e\u76ee\u7684\u306e\u305f\u3081\u306b\u3001house.csv<\/code>\u30d5\u30a1\u30a4\u30eb\u304b\u3089\u30c7\u30fc\u30bf\u3092\u53d6\u5f97\u3057\u3001GridDB\u306b\u30d7\u30c3\u30b7\u30e5\u3057\u307e\u3059\u3002\u6b21\u306e\u30b3\u30fc\u30c9\u30d6\u30ed\u30c3\u30af\u304c\u3053\u306e\u30bf\u30b9\u30af\u3092\u5b9f\u884c\u3057\u307e\u3059\u3002<\/p>\n\n
\nFile file1 = new File(\"house.csv\");\nScanner scan = new Scanner(file1);\nString data = scan.next();\n\nwhile (scan.hasNext()){\n String scanData = scan.next();\n String dataList[] = scanData.split(\",\");\n String housesize = dataList[0];\n String lotsize = dataList[1];\n String bedrooms = dataList[2];\n String granite = dataList[3];\n String bathroom = dataList[4];\n String sellingprice = dataList[5];\n \n House hs = new House();\n \n hs.housesize = Integer.parseInt(housesize);\n hs.lotsize = Integer.parseInt(lotsize);\n hs.bedrooms = Integer.parseInt(bedrooms);\n hs.granite = Integer.parseInt(granite);\n hs.bathroom = Integer.parseInt(bathroom);\n hs.sellingprice = Integer.parseInt(sellingprice);\n coll.put(hs);\n}<\/code><\/pre>\n<\/div>\n\u30b3\u30f3\u30c6\u30ca\u306b\u30c7\u30fc\u30bf\u3092\u30d7\u30c3\u30b7\u30e5\u3059\u308b\u305f\u3081\u306b\u3001\u30b9\u30ad\u30fc\u30de\u30af\u30e9\u30b9 House<\/code> \u306e\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u4f5c\u6210\u3057\u307e\u3057\u305f\u3002<\/p>\nGridDB \u304b\u3089\u30c7\u30fc\u30bf\u3092\u53d6\u5f97<\/h2>\n
GridDB \u30b3\u30f3\u30c6\u30ca\u304b\u3089\u30c7\u30fc\u30bf\u3092\u53d6\u5f97\u3057\u3001\u5206\u6790\u3067\u304d\u308b\u3088\u3046\u306b\u3057\u307e\u3057\u3087\u3046\u3002\u4ee5\u4e0b\u306e\u30b3\u30fc\u30c9\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002<\/p>\n
\n
\nQuery query = coll.query(\"select *\");\nRowSet<house> rs = query.fetch(false);<\/house><\/code><\/pre>\n<\/div>\nGridDB\u304b\u3089\u306e\u30af\u30a8\u30ea\u30c7\u30fc\u30bf\u306f\u4e00\u822c\u7684\u306aSQL\u30af\u30a8\u30ea\u3068\u4f3c\u3066\u3044\u307e\u3059\u3002\u3053\u3053\u3067\u306f\u3001select *<\/code>\u30af\u30a8\u30ea\u3092\u4f7f\u7528\u3057\u3066\u3001GridDB\u30b3\u30f3\u30c6\u30ca\u304b\u3089\u3059\u3079\u3066\u306e\u30c7\u30fc\u30bf\u3092\u53d6\u5f97\u3057\u307e\u3057\u305f\u3002<\/p>\n\u3053\u308c\u3089\u306e\u30c7\u30fc\u30bf\u3092\u6b21\u306e\u30b9\u30c6\u30c3\u30d7\u3067\u4f7f\u7528\u3059\u308b\u305f\u3081\u306b\u3001\u6587\u5b57\u5217\u306b\u4fdd\u5b58\u3057\u307e\u3059\u3002<\/p>\n
\n
\nString datastr = \"@RELATION housenn@ATTRIBUTE houseSize NUMERICn@ATTRIBUTE lotSize NUMERICn@ATTRIBUTE bedrooms NUMERICn@ATTRIBUTE granite NUMERICn@ATTRIBUTE bathroom NUMERICn@ATTRIBUTE sellingPrice NUMERICnn@DATAn\";\n\nwhile (rs.hasNext()) {\nHouse hs = rs.next();\ndatastr = datastr + hs.housesize+\",\"+hs.lotsize+\",\"+hs.bedrooms+\",\"+hs.granite+\",\"+hs.bathroom+\",\"+hs.sellingprice+\"n\";\n}<\/code><\/pre>\n<\/div>\n\u6587\u5b57\u5217 datastr<\/code> \u3092 arff<\/code> \u30d5\u30a1\u30a4\u30eb\u69cb\u9020\u3067\u521d\u671f\u5316\u3057\u3066\u3044\u308b\u3053\u3068\u306b\u6ce8\u76ee\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n\u6b63\u898f\u5316\u524d\u306e\u30c7\u30fc\u30bf\u304c\u3069\u306e\u3088\u3046\u306a\u3082\u306e\u304b\u898b\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n
\n
\nSystem.out.println(\"==== Before Normalization ===n\"+datastr);<\/code><\/pre>\n<\/div>\nWeka \u30a4\u30f3\u30b9\u30bf\u30f3\u30b9\u306e\u4f5c\u6210<\/h2>\n
\u30c7\u30fc\u30bf\u306e\u6b63\u898f\u5316\u306b\u306f\u3001Weka \u30de\u30b7\u30f3\u30e9\u30fc\u30cb\u30f3\u30b0\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002\u305d\u306e\u305f\u3081\u3001\u30c7\u30fc\u30bf\u3092 Weka \u30a4\u30f3\u30b9\u30bf\u30f3\u30b9\u306b\u5909\u63db\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n
\u524d\u56de\u306e\u30b9\u30c6\u30c3\u30d7\u3067\u3001\u30c7\u30fc\u30bf\u3092\u6587\u5b57\u5217 datastr<\/code> \u306b\u683c\u7d0d\u3057\u305f\u3053\u3068\u3092\u899a\u3048\u3066\u3044\u307e\u3059\u304b?<\/p>\n\u306f\u3044\u3001\u305d\u306e\u6587\u5b57\u5217\u3092 Weka \u30a4\u30f3\u30b9\u30bf\u30f3\u30b9\u306b\u6e21\u3057\u307e\u3059\u3002<\/p>\n
\n
\nReader dataString = new StringReader(datastr);\nInstances dataset = new Instances(dataString);\ndataset.setClassIndex(dataset.numAttributes()-1);<\/code><\/pre>\n<\/div>\n\u4e0a\u8a18\u306e\u30b3\u30fc\u30c9\u306fWeka\u30a4\u30f3\u30b9\u30bf\u30f3\u30b9\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002<\/p>\n
\u6b63\u898f\u5316<\/h2>\n
\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306b\u6b63\u898f\u5316\u3092\u5b9f\u884c\u3057\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n
\n
\nNormalize normalize = new Normalize();\nnormalize.setInputFormat(dataset);\nInstances newdata = Filter.useFilter(dataset, normalize);<\/code><\/pre>\n<\/div>\n\u6b21\u306b\u3001\u6b63\u898f\u5316\u5f8c\u306e\u30c7\u30fc\u30bf\u306e\u53ef\u8996\u5316\u3092\u884c\u3044\u307e\u3059\u3002<\/p>\n
\n
\nSystem.out.println(\"==== After Normalization ===n\"+newdata);<\/code><\/pre>\n<\/div>\n\u6700\u5f8c\u306b\u3001\u6b63\u898f\u5316\u3055\u308c\u305f\u30c7\u30fc\u30bf\u306b\u7dda\u5f62\u56de\u5e30\u3092\u9069\u7528\u3057\u305f\u3060\u3051\u3067\u3059\u3002<\/p>\n
\n
\nLinearRegression lr = new LinearRegression();\nlr.buildClassifier(newdata);\nEvaluation lreval = new Evaluation(newdata);\nlreval.evaluateModel(lr, newdata);\nSystem.out.println(lreval.toSummaryString());<\/code><\/pre>\n<\/div>\n\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u306b\u3064\u3044\u3066\u306f\u4ee5\u4e0a\u3067\u3059\u3002\u30c6\u30b9\u30c8\u3057\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n
\u30b3\u30f3\u30d1\u30a4\u30eb\u3068\u5b9f\u884c<\/h2>\n
IDE\u3092\u4f7f\u7528\u3057\u3066\u3044\u306a\u3044\u5834\u5408\u306f\u3001JAR\u30d5\u30a1\u30a4\u30eb\u3092\u30af\u30e9\u30b9\u30d1\u30b9\u306b\u542b\u3081\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n
\n
\nexport CLASSPATH=$CLASSPATH:\/Home\/User\/Download\/gridstore.jar<\/code><\/pre>\n<\/div>\n\n
\nexport CLASSPATH=$CLASSPATH:\/Home\/User\/Download\/weka-3.7.0.jar<\/code><\/pre>\n<\/div>\n\u3053\u308c\u3089\u306e\u30d1\u30b9\u306f\u3001\u304a\u5ba2\u69d8\u306e\u8a2d\u5b9a\u306b\u3088\u3063\u3066\u7570\u306a\u308b\u5834\u5408\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n
\u3053\u306e\u30b3\u30de\u30f3\u30c9\u3092\u4f7f\u7528\u3057\u3066\u30b3\u30fc\u30c9\u3092\u30b3\u30f3\u30d1\u30a4\u30eb\u3067\u304d\u307e\u3059\u3002<\/p>\n
\n
\njavac NormalizationJava.java<\/code><\/pre>\n<\/div>\n\u6b21\u306b\u30b3\u30fc\u30c9\u3092\u5b9f\u884c\u3057\u307e\u3059\u3002<\/p>\n
\n
\njava NormalizationJava<\/code><\/pre>\n<\/div>\n\u51fa\u529b\u306e\u8868\u793a<\/h2>\n
\u30b3\u30fc\u30c9\u3092\u5b9f\u884c\u3059\u308b\u3068\u3001\u4ee5\u4e0b\u306e\u51fa\u529b\u304c\u5f97\u3089\u308c\u307e\u3059\u3002<\/p>\n
\n
\n==== Before Normalization ===\n@RELATION house\n\n@ATTRIBUTE houseSize NUMERIC\n@ATTRIBUTE lotSize NUMERIC\n@ATTRIBUTE bedrooms NUMERIC\n@ATTRIBUTE granite NUMERIC\n@ATTRIBUTE bathroom NUMERIC\n@ATTRIBUTE sellingPrice NUMERIC\n\n@DATA\n3247,10061,5,1,1,224900\n2397,14156,4,1,0,189900\n3536,19994,6,1,1,325000\n3529,9191,6,0,0,205000\n4032,10150,5,0,1,197900\n2200,9600,4,0,1,195000\n2983,9365,5,0,1,230000\n\n==== After Normalization ===\n@relation house-weka.filters.unsupervised.attribute.Normalize-S1.0-T0.0\n\n@attribute houseSize numeric\n@attribute lotSize numeric\n@attribute bedrooms numeric\n@attribute granite numeric\n@attribute bathroom numeric\n@attribute sellingPrice numeric\n\n@data\n0.571507,0.080533,0.5,1,1,224900\n0.107533,0.459595,0,1,0,189900\n0.729258,1,1,1,1,325000\n0.725437,0,1,0,0,205000\n1,0.088772,0.5,0,1,197900\n0,0.03786,0,0,1,195000\n0.427402,0.016107,0.5,0,1,230000\n\nCorrelation coefficient 0.9945\nMean absolute error 4053.821 \nRoot mean squared error 4578.4125\nRelative absolute error 13.1339 %\nRoot relative squared error 10.51 %\nTotal Number of Instances 7 \n\nBUILD SUCCESSFUL (total time: 1 second)<\/code><\/pre>\n<\/div>\n\u307e\u3068\u3081<\/h2>\n
\u4ee5\u4e0a\u3067\u3001GridDB \u3092\u4f7f\u7528\u3057\u305f Java \u3067\u306e\u6b63\u898f\u5316\u306e\u8aac\u660e\u3092\u7d42\u308f\u308a\u307e\u3059\u3002<\/p>\n
\u3053\u306e\u8a18\u4e8b\u3067\u306f\u3001\u3088\u308a\u826f\u3044\u5206\u6790\u3092\u884c\u3046\u305f\u3081\u306b\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306b\u6b63\u898f\u5316\u3092\u9069\u7528\u3059\u308b\u65b9\u6cd5\u3092\u8aac\u660e\u3057\u307e\u3057\u305f\u3002\u524d\u8ff0\u306e\u3068\u304a\u308a\u3001\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306b\u3055\u307e\u3056\u307e\u306a\u7279\u6027\u304c\u542b\u307e\u308c\u308b\u5834\u5408\u3001\u6b63\u898f\u5316\u304c\u5f79\u7acb\u3061\u307e\u3059\u3002<\/p>\n
\u6700\u5f8c\u306b\u3001\u30af\u30a8\u30ea\u3001\u30b3\u30f3\u30c6\u30ca\u3001\u304a\u3088\u3073 GridDB \u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u3092\u78ba\u5b9f\u306b\u9589\u3058\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n
\n
\nquery.close();\ncoll.close();\nstore.close();<\/code><\/pre>\n<\/div>\n","protected":false},"excerpt":{"rendered":"\u672c\u30d6\u30ed\u30b0\u3067\u306f\u3001Java\u3068GridDB\u3092\u4f7f\u7528\u3057\u3066\u6a5f\u68b0\u5b66\u7fd2\u7528\u306e\u30c7\u30fc\u30bf\u6b63\u898f\u5316\u3092\u5b9f\u6f14\u3057\u307e\u3059\u3002 \u672c\u30d6\u30ed\u30b0\u306e\u30bd\u30fc\u30b9\u30b3\u30fc\u30c9\u306f\u3001\u5f53\u793e\u306eGitHub\u30da\u30fc\u30b8\u3067\u3054\u89a7\u3044\u305f\u3060\u3051\u307e\u3059:https:\/\/github.com\/griddbnet\/Blo […]<\/p>\n","protected":false},"author":41,"featured_media":49710,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1005],"tags":[],"class_list":["post-50907","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-1005"],"acf":[],"yoast_head":"\n
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