Comments (3)
haifengl
commented on June 22, 2024
Thanks for reporting. But I cannot reproduce the issue. Here is the output of your code in jshell:
jshell> smile.regression.RandomForest model = smile.regression.RandomForest.fit(formula, data, 100, 3, 20, 10, 3, 1.0, Arrays.stream(seeds));
[ForkJoinPool.commonPool-worker-6] INFO smile.regression.RandomForest - Regression tree OOB R2: 92.68%
[ForkJoinPool.commonPool-worker-5] INFO smile.regression.RandomForest - Regression tree OOB R2: 92.50%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 95.29%
[ForkJoinPool.commonPool-worker-4] INFO smile.regression.RandomForest - Regression tree OOB R2: 45.31%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 72.80%
[ForkJoinPool.commonPool-worker-4] INFO smile.regression.RandomForest - Regression tree OOB R2: 96.00%
[ForkJoinPool.commonPool-worker-6] INFO smile.regression.RandomForest - Regression tree OOB R2: -52.84%
[ForkJoinPool.commonPool-worker-4] INFO smile.regression.RandomForest - Regression tree OOB R2: 79.68%
[ForkJoinPool.commonPool-worker-6] INFO smile.regression.RandomForest - Regression tree OOB R2: 84.25%
[ForkJoinPool.commonPool-worker-4] INFO smile.regression.RandomForest - Regression tree OOB R2: 80.84%
[ForkJoinPool.commonPool-worker-4] INFO smile.regression.RandomForest - Regression tree OOB R2: 94.74%
[ForkJoinPool.commonPool-worker-5] INFO smile.regression.RandomForest - Regression tree OOB R2: 81.39%
[ForkJoinPool.commonPool-worker-4] INFO smile.regression.RandomForest - Regression tree OOB R2: 52.97%
[ForkJoinPool.commonPool-worker-5] INFO smile.regression.RandomForest - Regression tree OOB R2: 19.96%
[ForkJoinPool.commonPool-worker-4] INFO smile.regression.RandomForest - Regression tree OOB R2: 94.88%
[ForkJoinPool.commonPool-worker-5] INFO smile.regression.RandomForest - Regression tree OOB R2: 77.90%
[ForkJoinPool.commonPool-worker-4] INFO smile.regression.RandomForest - Regression tree OOB R2: 80.58%
[ForkJoinPool.commonPool-worker-5] INFO smile.regression.RandomForest - Regression tree OOB R2: 65.82%
[ForkJoinPool.commonPool-worker-4] INFO smile.regression.RandomForest - Regression tree OOB R2: -0.68%
[ForkJoinPool.commonPool-worker-5] INFO smile.regression.RandomForest - Regression tree OOB R2: 85.60%
[ForkJoinPool.commonPool-worker-4] INFO smile.regression.RandomForest - Regression tree OOB R2: 94.41%
[ForkJoinPool.commonPool-worker-5] INFO smile.regression.RandomForest - Regression tree OOB R2: 86.14%
[ForkJoinPool.commonPool-worker-4] INFO smile.regression.RandomForest - Regression tree OOB R2: 94.58%
[ForkJoinPool.commonPool-worker-6] INFO smile.regression.RandomForest - Regression tree OOB R2: 69.15%
[ForkJoinPool.commonPool-worker-5] INFO smile.regression.RandomForest - Regression tree OOB R2: 47.19%
[ForkJoinPool.commonPool-worker-6] INFO smile.regression.RandomForest - Regression tree OOB R2: 64.80%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 50.14%
[ForkJoinPool.commonPool-worker-4] INFO smile.regression.RandomForest - Regression tree OOB R2: 91.10%
[ForkJoinPool.commonPool-worker-6] INFO smile.regression.RandomForest - Regression tree OOB R2: 66.80%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 82.73%
[ForkJoinPool.commonPool-worker-4] INFO smile.regression.RandomForest - Regression tree OOB R2: 71.68%
[ForkJoinPool.commonPool-worker-6] INFO smile.regression.RandomForest - Regression tree OOB R2: 71.86%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 82.10%
[ForkJoinPool.commonPool-worker-4] INFO smile.regression.RandomForest - Regression tree OOB R2: 37.68%
[ForkJoinPool.commonPool-worker-6] INFO smile.regression.RandomForest - Regression tree OOB R2: 90.01%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 44.82%
[ForkJoinPool.commonPool-worker-4] INFO smile.regression.RandomForest - Regression tree OOB R2: 89.69%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 89.96%
[ForkJoinPool.commonPool-worker-6] INFO smile.regression.RandomForest - Regression tree OOB R2: 86.88%
[ForkJoinPool.commonPool-worker-4] INFO smile.regression.RandomForest - Regression tree OOB R2: 68.18%
[ForkJoinPool.commonPool-worker-6] INFO smile.regression.RandomForest - Regression tree OOB R2: 80.44%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: -67.39%
[ForkJoinPool.commonPool-worker-6] INFO smile.regression.RandomForest - Regression tree OOB R2: 83.29%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 68.86%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: -52.48%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 69.99%
[ForkJoinPool.commonPool-worker-5] INFO smile.regression.RandomForest - Regression tree OOB R2: 52.94%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 88.30%
[ForkJoinPool.commonPool-worker-5] INFO smile.regression.RandomForest - Regression tree OOB R2: 76.42%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 46.09%
[ForkJoinPool.commonPool-worker-5] INFO smile.regression.RandomForest - Regression tree OOB R2: 88.84%
[ForkJoinPool.commonPool-worker-6] INFO smile.regression.RandomForest - Regression tree OOB R2: 94.47%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 90.22%
[ForkJoinPool.commonPool-worker-6] INFO smile.regression.RandomForest - Regression tree OOB R2: 44.55%
[ForkJoinPool.commonPool-worker-5] INFO smile.regression.RandomForest - Regression tree OOB R2: 73.57%
[ForkJoinPool.commonPool-worker-6] INFO smile.regression.RandomForest - Regression tree OOB R2: 71.46%
[ForkJoinPool.commonPool-worker-6] INFO smile.regression.RandomForest - Regression tree OOB R2: 56.63%
[ForkJoinPool.commonPool-worker-6] INFO smile.regression.RandomForest - Regression tree OOB R2: 94.19%
[ForkJoinPool.commonPool-worker-6] INFO smile.regression.RandomForest - Regression tree OOB R2: 85.09%
[ForkJoinPool.commonPool-worker-6] INFO smile.regression.RandomForest - Regression tree OOB R2: 48.94%
[ForkJoinPool.commonPool-worker-4] INFO smile.regression.RandomForest - Regression tree OOB R2: 59.37%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 86.04%
[ForkJoinPool.commonPool-worker-5] INFO smile.regression.RandomForest - Regression tree OOB R2: 91.90%
[ForkJoinPool.commonPool-worker-6] INFO smile.regression.RandomForest - Regression tree OOB R2: 77.22%
[ForkJoinPool.commonPool-worker-5] INFO smile.regression.RandomForest - Regression tree OOB R2: 68.18%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 72.97%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 42.43%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 88.18%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 89.88%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 75.93%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 63.56%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 82.64%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 79.55%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: -592.92%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: -40.05%
[ForkJoinPool.commonPool-worker-6] INFO smile.regression.RandomForest - Regression tree OOB R2: 92.73%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 72.49%
[ForkJoinPool.commonPool-worker-6] INFO smile.regression.RandomForest - Regression tree OOB R2: 80.21%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 75.78%
[ForkJoinPool.commonPool-worker-5] INFO smile.regression.RandomForest - Regression tree OOB R2: 81.12%
[ForkJoinPool.commonPool-worker-5] INFO smile.regression.RandomForest - Regression tree OOB R2: 81.77%
[ForkJoinPool.commonPool-worker-5] INFO smile.regression.RandomForest - Regression tree OOB R2: 84.95%
[ForkJoinPool.commonPool-worker-4] INFO smile.regression.RandomForest - Regression tree OOB R2: 84.55%
[ForkJoinPool.commonPool-worker-5] INFO smile.regression.RandomForest - Regression tree OOB R2: 77.15%
[ForkJoinPool.commonPool-worker-4] INFO smile.regression.RandomForest - Regression tree OOB R2: 44.95%
[ForkJoinPool.commonPool-worker-5] INFO smile.regression.RandomForest - Regression tree OOB R2: 81.46%
[ForkJoinPool.commonPool-worker-4] INFO smile.regression.RandomForest - Regression tree OOB R2: 42.47%
[ForkJoinPool.commonPool-worker-4] INFO smile.regression.RandomForest - Regression tree OOB R2: 79.70%
[ForkJoinPool.commonPool-worker-4] INFO smile.regression.RandomForest - Regression tree OOB R2: 76.79%
[ForkJoinPool.commonPool-worker-6] INFO smile.regression.RandomForest - Regression tree OOB R2: 16.79%
[ForkJoinPool.commonPool-worker-4] INFO smile.regression.RandomForest - Regression tree OOB R2: 13.83%
[ForkJoinPool.commonPool-worker-6] INFO smile.regression.RandomForest - Regression tree OOB R2: 89.02%
[ForkJoinPool.commonPool-worker-4] INFO smile.regression.RandomForest - Regression tree OOB R2: 83.28%
[ForkJoinPool.commonPool-worker-6] INFO smile.regression.RandomForest - Regression tree OOB R2: -147.08%
[ForkJoinPool.commonPool-worker-4] INFO smile.regression.RandomForest - Regression tree OOB R2: 50.39%
[ForkJoinPool.commonPool-worker-6] INFO smile.regression.RandomForest - Regression tree OOB R2: 30.56%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 94.31%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 91.06%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 58.76%
[main] INFO smile.regression.RandomForest - Regression tree OOB R2: 55.30%
from smile.
smpawlowski
commented on June 22, 2024
Hi! I run into similar issue when trying to upgrade from 2.6.0 to 3.1.0. Predict requires DataFrame that contains the predicted variable. Code below works in 2.6.0, but not 3.1.0.
`
import org.junit.Assert;
import org.junit.Test;
import smile.data.DataFrame;
import smile.data.formula.Formula;
import smile.data.vector.DoubleVector;
import smile.regression.LinearModel;
import smile.regression.OLS;
public class TestSmileRegression {
@Test
public void test_formula_OLS() {
double[] x = {1, 2, 3};
double[] y = {1, 2, 3};
DataFrame df = DataFrame.of(DoubleVector.of("x", x),
DoubleVector.of("y", y));
LinearModel regr = OLS.fit(Formula.lhs("y"), df);
double[] x_pred = {4,5,6};
double[] y_pred = regr.predict(DataFrame.of( DoubleVector.of("x", x_pred)));
for(int i=0; i<x_pred.length; i++) {
Assert.assertEquals(x_pred[i], y_pred[i], 1e-9);
}
}
}`
Exception:
`java.lang.IllegalArgumentException: Field y doesn't exist
at smile.data.type.StructType.indexOf(StructType.java:103)
at smile.data.formula.Variable$1.<init>(Variable.java:80)
at smile.data.formula.Variable.bind(Variable.java:78)
at smile.data.formula.Formula.bind(Formula.java:360)
at smile.data.formula.Formula.x(Formula.java:497)
at smile.data.formula.Formula.matrix(Formula.java:546)
at smile.regression.LinearModel.predict(LinearModel.java:358)
at models.TestSmileRegression.test_formula_OLS(TestSmileRegression.java:22)
`
from smile.
ProtossidoDiAzoto
commented on June 22, 2024
yes exactly "predict requires DataFrame that contains the predicted variable" indeed I had solved the issue the past week by implementing the following solution:
@Test
public void tryOutRandomForestArrayData(){
MathEx.setSeed(19650218);
RandomForest model = RandomForest.fit(formula, data, 100, 3, 20, 10, 3, 1.0, Arrays.stream(seeds));
List<StructField> fields = Arrays.asList(
new StructField("GNP", DataTypes.DoubleType),
new StructField("unemployed", DataTypes.DoubleType),
new StructField("armed_forces", DataTypes.DoubleType),
new StructField("population", DataTypes.DoubleType),
new StructField("year", DataTypes.IntegerType),
new StructField("employed", DataTypes.DoubleType),
new StructField("deflator", DataTypes.DoubleType)
);
StructType st = new StructType(fields);
for (int i = 0; i < x.length; i++) {
Tuple param = Tuple.of(x[i],st);
System.out.println(model.predict(param));
}
}
from smile.
Related Issues (20)
- Dot product Question HOT 2
- stringVector(0) error HOT 1
- Suggest changing license to Apache 2.0 license or MIT
- Non-monotonic cluster tree -- the linkage is probably not appropriate! HOT 1
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- Method in interface BaseArray can never return an int[] HOT 2
- Making the plot module available in Java API HOT 4
- InnerProduct of vectors created with cas.Vars not being simplified HOT 6
- Support header attribute on facet / row / column encoding channels HOT 2
- Incorrect spec generated for encoding channel sort HOT 4
- How can I set up in Intellij or other IDE to compile and read code? HOT 3
- What is the efficient way to fill null values in a column with an arbitrary string in a Dataframe? HOT 3
- ClassCastException when calling DataFrame.omitNullRows() HOT 1
- smile.plot.swing.BarPlot works with smile-plot 3.0.2 but not with 3.1.0 HOT 2
- IllegalArgumentException when suing SimpleImputer for data sourced from json file HOT 1
- Is there any possibility to use ID3 or C4.5 via the Smile Package in Java? HOT 1
- F1, precision & recall for multi-class classification HOT 5
- Predict requires DataFrame that contains the predicted variable in 3.1.0 HOT 5
- Suspicious discontinuity in run time with LU decomposition HOT 2
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