package vega
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- def bar(data: (String, Array[Double]), group: (String, Array[String]), properties: JsObject): JsObject
- def bar(data: Array[Double]): JsObject
- def boxplot(data: (String, Array[Double]), group: (String, Array[String]), properties: JsObject): JsObject
- def embed(spec: JsObject): String
- def hist(x: (String, Array[Double]), k: Int, properties: JsObject): JsObject
- def iframe(spec: JsObject, id: String): String
- def line(data: Array[Array[Double]], fields: (String, String), point: Boolean, color: Option[(String, Either[Array[Int], Array[String]])], shape: Option[(String, Either[Array[Int], Array[String]])], properties: JsObject): JsObject
- implicit def pimpDataFrame(data: DataFrame): DataFrame2JSON
- implicit def pimpTuple(data: Tuple): Tuple2JSON
- def plot(data: Array[Array[Double]], fields: (String, String), color: Option[(String, Either[Array[Int], Array[String]])], shape: Option[(String, Either[Array[Int], Array[String]])], sizeOrText: Option[(String, Either[Array[Double], Array[String]])], properties: JsObject): JsObject
- def spm(data: DataFrame, clazz: Option[String], properties: JsObject): JsObject
- object Window extends LazyLogging with Serializable
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.