Class RegressionNode

java.lang.Object
smile.base.cart.LeafNode
smile.base.cart.RegressionNode
All Implemented Interfaces:
Serializable, Node

public class RegressionNode extends LeafNode
A leaf node in regression tree.
See Also:
  • Constructor Details

    • RegressionNode

      public RegressionNode(int size, double output, double mean, double rss)
      Constructor.
      Parameters:
      size - the number of samples in the node
      output - the predicted value for this node.
      mean - the mean of response variable.
      rss - the residual sum of squares.
  • Method Details

    • output

      public double output()
      Returns the predicted value.
      Returns:
      the predicted value.
    • mean

      public double mean()
      Returns the mean of response variable.
      Returns:
      the mean of response variable.
    • impurity

      public double impurity()
      Returns the residual sum of squares.
      Returns:
      the residual sum of squares.
    • deviance

      public double deviance()
      Description copied from interface: Node
      Returns the deviance of node.
      Returns:
      the deviance of node.
    • dot

      public String dot(StructType schema, StructField response, int id)
      Description copied from interface: Node
      Returns the dot representation of node.
      Parameters:
      schema - the schema of data
      response - the schema of response variable
      id - node id
      Returns:
      the dot representation of node.
    • toString

      public int[] toString(StructType schema, StructField response, InternalNode parent, int depth, BigInteger id, List<String> lines)
      Description copied from interface: Node
      Adds the string representation (R's rpart format) to a collection.
      Parameters:
      schema - the schema of data
      response - the schema of response variable
      parent - the parent node
      depth - the depth of node in the tree. The root node is at depth 0.
      id - node id
      lines - the collection of node's string representation.
      Returns:
      the sample count of each class for decision tree; single element array [node size] for regression tree.
    • equals

      public boolean equals(Object o)
      Overrides:
      equals in class Object