trait JWindow extends AnyRef
JFrame window.
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- final def !=(arg0: Any): Boolean
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- AnyRef → Any
- final def ##: Int
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- AnyRef → Any
- def +(other: String): String
- def ->[B](y: B): (JWindow, B)
- final def ==(arg0: Any): Boolean
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- def clone(): AnyRef
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- @throws(classOf[java.lang.CloneNotSupportedException]) @native()
- def close: Unit
Closes the window programmatically.
- def ensuring(cond: (JWindow) => Boolean, msg: => Any): JWindow
- def ensuring(cond: (JWindow) => Boolean): JWindow
- def ensuring(cond: Boolean, msg: => Any): JWindow
- def ensuring(cond: Boolean): JWindow
- final def eq(arg0: AnyRef): Boolean
- Definition Classes
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- def equals(arg0: AnyRef): Boolean
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- def finalize(): Unit
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- @throws(classOf[java.lang.Throwable])
- def formatted(fmtstr: String): String
- final def getClass(): Class[_ <: AnyRef]
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- AnyRef → Any
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- @native()
- def hashCode(): Int
- Definition Classes
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- @native()
- final def isInstanceOf[T0]: Boolean
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- final def ne(arg0: AnyRef): Boolean
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- final def notify(): Unit
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- final def notifyAll(): Unit
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- @native()
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
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- def toString(): String
- Definition Classes
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- final def wait(): Unit
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- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long, arg1: Int): Unit
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- final def wait(arg0: Long): Unit
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- @throws(classOf[java.lang.InterruptedException]) @native()
Deprecated Value Members
- def →[B](y: B): (JWindow, B)
- Implicit
- This member is added by an implicit conversion from JWindow toArrowAssoc[JWindow] performed by method ArrowAssoc in scala.Predef.
- Definition Classes
- ArrowAssoc
- Annotations
- @deprecated
- Deprecated
(Since version 2.13.0) Use
->
instead. If you still wish to display it as one character, consider using a font with programming ligatures such as Fira Code.
Smile (Statistical Machine Intelligence and Learning Engine) is a fast and comprehensive machine learning, NLP, linear algebra, graph, interpolation, and visualization system in Java and Scala. With advanced data structures and algorithms, Smile delivers state-of-art performance.
Smile covers every aspect of machine learning, including classification, regression, clustering, association rule mining, feature selection, manifold learning, multidimensional scaling, genetic algorithms, missing value imputation, efficient nearest neighbor search, etc.