+ 1
Drag and drop from the options below to print "Hello".
class A { public void print() { System.out.println("A"); } } class B { public static void main(String[ ] args) { object = A() { @Override public void () { System.out.println(); } }; object.print(); } }
6 Antworten
+ 4
A,new,print,hello
+ 2
A object = new A() {
@Override public void print() {
System.out.println("Hello");
}
+ 1
class A {
public void print() {
System.out.println("A");
}
}
class B {
public static void main(String[ ] args) {
object = A() {
@Override public void () {
System.out.println();
}
};
object.print();
}
0
Drag and drop to scale features for the wine dataset:
from sklearn.preprocessing
import StandardScaler
scale = StandardScaler()
scale.fit(X)
X_scaled =transformscale.(X)
0
Drag and drop to complete the pre-processing step to standardize the wine data.
from sklearn.preprocessing
import StandardScaler
X = wine[['alcohol', 'total_phenols']]
scale = StandardScaler()
scale.fit(X)
X_scaled = scale.transform(X)
0
String
var