Column 4 is always constant, so no predictive power resulting zero weight. On Sunday, October 25, 2015, Zhiliang Zhu <zchl.j...@yahoo.com> wrote:
> Hi DB Tsai, > > Thanks very much for your kind reply help. > > As for your comment, I just modified and tested the key part of the codes: > > LinearRegression lr = new LinearRegression() > .setMaxIter(10000) > .setRegParam(0) > .setElasticNetParam(0); //the number could be reset > > final LinearRegressionModel model = lr.fit(training); > > Now the output is much reasonable, however, x4 is always 0 while > repeatedly reset those parameters in lr , would you help some about it how > to properly set the parameters ... > > Final w: [1.000000127825909,1.999999979185054,2.999999993307136,0.0] > > Thank you, > Zhiliang > > > > > On Monday, October 26, 2015 5:14 AM, DB Tsai <dbt...@dbtsai.com > <javascript:_e(%7B%7D,'cvml','dbt...@dbtsai.com');>> wrote: > > > LinearRegressionWithSGD is not stable. Please use linear regression in > ML package instead. > http://spark.apache.org/docs/latest/ml-linear-methods.html > > Sincerely, > > DB Tsai > ---------------------------------------------------------- > Web: https://www.dbtsai.com > PGP Key ID: 0xAF08DF8D > > > On Sun, Oct 25, 2015 at 10:14 AM, Zhiliang Zhu > <zchl.j...@yahoo.com.invalid > <javascript:_e(%7B%7D,'cvml','zchl.j...@yahoo.com.invalid');>> wrote: > > Dear All, > > > > I have some program as below which makes me very much confused and > > inscrutable, it is about multiple dimension linear regression mode, the > > weight / coefficient is always perfect while the dimension is smaller > than > > 4, otherwise it is wrong all the time. > > Or, whether the LinearRegressionWithSGD would be selected for another > one? > > > > public class JavaLinearRegression { > > public static void main(String[] args) { > > SparkConf conf = new SparkConf().setAppName("Linear Regression > > Example"); > > JavaSparkContext sc = new JavaSparkContext(conf); > > SQLContext jsql = new SQLContext(sc); > > > > //Ax = b, x = [1, 2, 3, 4] would be the only one output about weight > > //x1 + 2 * x2 + 3 * x3 + 4 * x4 = y would be the multiple linear mode > > List<LabeledPoint> localTraining = Lists.newArrayList( > > new LabeledPoint(30.0, Vectors.dense(1.0, 2.0, 3.0, 4.0)), > > new LabeledPoint(29.0, Vectors.dense(0.0, 2.0, 3.0, 4.0)), > > new LabeledPoint(25.0, Vectors.dense(0.0, 0.0, 3.0, 4.0)), > > new LabeledPoint(16.0, Vectors.dense(0.0, 0.0, 0.0, 4.0))); > > > > JavaRDD<LabeledPoint> training = > sc.parallelize(localTraining).cache(); > > > > // Building the model > > int numIterations = 1000; //the number could be reset large > > final LinearRegressionModel model = > > LinearRegressionWithSGD.train(JavaRDD.toRDD(training), numIterations); > > > > //the coefficient weights are perfect while dimension of LabeledPoint > is > > SMALLER than 4. > > //otherwise the output is always wrong and inscrutable. > > //for instance, one output is > > //Final w: > > > [2.537341836047772E25,-7.744333206289736E24,6.697875883454909E23,-2.6704705246777624E22] > > System.out.print("Final w: " + model.weights() + "\n\n"); > > } > > } > > > > I would appreciate your kind help or guidance very much~~ > > > > Thank you! > > Zhiliang > > > > > > > -- - DB Sent from my iPhone
