ScatterPlot.of automatically choose color if you pass an array y.
@haifengl perhaps you could give a quick glance how to migrate the following piece of smile 2.2.x code into 2.5.x...
val canvas: PlotCanvas = smile.plot.swing.plot(data: Array[Array[Double]], label: Array[Int], legend: Array[Char], palette: Array[Color])
canvas.setAxisLabels(...)
canvas.setTitle(...)
PlotWindow.show("Clusters", canvas)In 2.5.1
- there is no corresponding signature of
plot - the return value changed from
PlotCanvastoCanvaswhich is no longer aJPanel
Thanks!
val iris = read.arff("data/weka/iris.arff")
val canvas = plot(iris, "sepallength", "sepalwidth", "class", '*')
canvas.setAxisLabels("sepallength", "sepalwidth")
show(canvas)smile.plot.show but rather assemble the swing components myself. In 2.2.x it was possible with PlotCanvas, in 2.5.x panel.add(canvas) no longer works. How do I make it work? Thanks!
2.5.1
PlotGrid for a grid of canvas
5 replies
SVM
Hi,I want to use SVM(linear) with OneVsOne strategy for binary classification.
I tried it with reading reference page(https://haifengl.github.io/classification.html), but I got errors from fit() methods.
T[] is a generic type object array, but I prepared DataFrame, what shold I do ?
public void trainSVM(DataFrame data, DataFrame label, String[] headerArrayThatSortedByImportance, int numOfSelection) {
String[] selectedFeatures = new String[numOfSelection];
for(int i=0;i<numOfSelection;i++) {
selectedFeatures[i] = headerArrayThatSortedByImportance[i];
}
double[][] x = data.select(selectedFeatures).toArray();
double[] y = label.toArray()[0];
double min = Arrays.stream(y).min().getAsDouble();
if(min==0) {
for(int i=0;i<y.length;i++) {
if(y[i]==0) {
y[i] = -1;
}
}
}
LinearKernel kernel = new LinearKernel();//GaussianKernel(8.0);
// I can not run here...
SVM model = OneVersusOne.fit(x, y, (x, y) -> SVM.fit( x, y,kernel, 1, 1E-3));
}@haifengl,
and user/developers
Hello,
SMILE is great product.
If you do not mind,please tell me how to do Group KFolds CrossValidation.
I found "GroupKFold" in API:http://haifengl.github.io/api/java/smile/validation/GroupKFold.html.
Then, I tried it, but I do not know following procedures,
1.I want to use SVM, what should I do/set parameters ?
int[] pred = new GropuKFold(1000,10,groups).classification(df, (??, ??) -> SVM.fit(????));
2.If I want visualize ROC curve, and calculate auc of each k, how to do that? When I use scikit-learn's GroupedkFold, I can load each folds dataset and can visualize all folds ROC with auc. By SMILE, how to perform?
Best regards,
13 replies
Sensitivity and Specificity
@haifengl
Hi, I have one question,
- Why SMILE Sensitivity.of() is return PPV ?
- Why SMILE Specificity.of() is return NPV ?
Or, my code is wrong ? (If so, so sory...)
Validation code is following,
int[] truth = new int[] {0,0,0,0,0,1,1,1,1,1};
int[] pred = new int[] {1,0,0,1,0,1,1,1,1,0};
ConfusionMatrix mtx = ConfusionMatrix.of(truth, pred);
System.out.println(mtx.toString());
int[][] mat = mtx.matrix;
double tn = mat[0][0];//tn
double fn = mat[0][1];//fn
double fp = mat[1][0];//fp
double tp = mat[1][1];//tp
double ppv = tp/(tp+fp);
double tpr = tp/(tp+fn);
double npv = tn/(tn+fn);
double spc = tn/(fp+tn);
System.out.println("TPR is "+tpr);//0.66
System.out.println("PPV is "+ppv);//0.8
System.out.println("SPC is "+spc);//0.75
System.out.println("NPV is "+npv);//0.6
System.out.println("Sensitivity is "+Sensitivity.of(truth, pred));//0.8
System.out.println("Specificity is "+Specificity.of(truth, pred));//0.6
HI Everyone, sorry for the newbie question but I'm kinda stuck here and didn't find a good way to work around the problem.
Basically I'm just trying to create a DataFrame from a SQL query but I keep getting an error:
val url = "jdbc:postgresql://localhost/test"
val props = Properties()
props.setProperty("user", "test")
props.setProperty("password", "test")
val conn: Connection = DriverManager.getConnection(url, props)
val rs = conn.createStatement().executeQuery("select 1 from homes")
val df = DataFrame.of(rs)
println(df)and the error:
Exception in thread "main" java.lang.IllegalArgumentException: No enum constant java.sql.JDBCType.int4
at java.base/java.lang.Enum.valueOf(Enum.java:240)
at java.sql/java.sql.JDBCType.valueOf(JDBCType.java:34)
at smile.data.type.DataTypes.struct(DataTypes.java:168)
at smile.data.type.DataTypes.struct(DataTypes.java:158)
at smile.data.DataFrame.of(DataFrame.java:1261)I'm using org.postgresql:postgresql:42.2.12
10 replies
Hi hifeng, I tried to use MultivariateGaussianMixture but have the following exception:
Warning: Could not load Loader: java.lang.UnsatisfiedLinkError: no jnijavacpp in java.library.path
Exception in thread "main" java.lang.UnsatisfiedLinkError: no jniopenblas_nolapack in java.library.path
I import the dependency in maven like this:
<dependency>
<groupId>com.github.haifengl</groupId>
<artifactId>smile-core</artifactId>
<version>2.5.3</version>
</dependency>
<!-- https://mvnrepository.com/artifact/org.bytedeco/javacpp -->
<dependency>
<groupId>org.bytedeco</groupId>
<artifactId>javacpp</artifactId>
<version>1.5.3</version>
</dependency>
<!-- https://mvnrepository.com/artifact/org.bytedeco/openblas -->
<dependency>
<groupId>org.bytedeco</groupId>
<artifactId>openblas</artifactId>
<version>0.3.9-1.5.3</version>
</dependency>
<!-- https://mvnrepository.com/artifact/org.bytedeco/arpack-ng -->
<dependency>
<groupId>org.bytedeco</groupId>
<artifactId>arpack-ng</artifactId>
<version>3.7.0-1.5.3</version>
</dependency>
new_col = lambda each_row: math.sqrt((3*each_row.first_column)**4 + (3*each_row.second_column)**4+ (3*each_row.third_column)**4)
my_dataframe.apply(new_col)
import smile.data.formula.Formula;
import static smile.data.formula.Terms.*;df.stream().map(row -> { or something?