本文整理汇总了Golang中github.com/shuLhan/tabula.ClasetInterface.MajorityClass方法的典型用法代码示例。如果您正苦于以下问题：Golang ClasetInterface.MajorityClass方法的具体用法？Golang ClasetInterface.MajorityClass怎么用？Golang ClasetInterface.MajorityClass使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类github.com/shuLhan/tabula.ClasetInterface的用法示例。
在下文中一共展示了ClasetInterface.MajorityClass方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Golang代码示例。
示例1: splitTreeByGain
/*
splitTreeByGain calculate the gain in all dataset, and split into two node:
left and right.
Return node with the split information.
*/
func (runtime *Runtime) splitTreeByGain(D tabula.ClasetInterface) (
node *binary.BTNode,
e error,
) {
node = &binary.BTNode{}
D.RecountMajorMinor()
// if dataset is empty return node labeled with majority classes in
// dataset.
nrow := D.GetNRow()
if nrow <= 0 {
if DEBUG >= 2 {
fmt.Printf("[cart] empty dataset (%s) : %v\n",
D.MajorityClass(), D)
}
node.Value = NodeValue{
IsLeaf: true,
Class: D.MajorityClass(),
Size: 0,
}
return node, nil
}
// if all dataset is in the same class, return node as leaf with class
// is set to that class.
single, name := D.IsInSingleClass()
if single {
if DEBUG >= 2 {
fmt.Printf("[cart] in single class (%s): %v\n", name,
D.GetColumns())
}
node.Value = NodeValue{
IsLeaf: true,
Class: name,
Size: nrow,
}
return node, nil
}
if DEBUG >= 2 {
fmt.Println("[cart] D:", D)
}
// calculate the Gini gain for each attribute.
gains := runtime.computeGain(D)
// get attribute with maximum Gini gain.
MaxGainIdx := gini.FindMaxGain(&gains)
MaxGain := gains[MaxGainIdx]
// if maxgain value is 0, use majority class as node and terminate
// the process
if MaxGain.GetMaxGainValue() == 0 {
if DEBUG >= 2 {
fmt.Println("[cart] max gain 0 with target",
D.GetClassAsStrings(),
" and majority class is ", D.MajorityClass())
}
node.Value = NodeValue{
IsLeaf: true,
Class: D.MajorityClass(),
Size: 0,
}
return node, nil
}
// using the sorted index in MaxGain, sort all field in dataset
tabula.SortColumnsByIndex(D, MaxGain.SortedIndex)
if DEBUG >= 2 {
fmt.Println("[cart] maxgain:", MaxGain)
}
// Now that we have attribute with max gain in MaxGainIdx, and their
// gain dan partition value in Gains[MaxGainIdx] and
// GetMaxPartValue(), we split the dataset based on type of max-gain
// attribute.
// If its continuous, split the attribute using numeric value.
// If its discrete, split the attribute using subset (partition) of
// nominal values.
var splitV interface{}
if MaxGain.IsContinu {
splitV = MaxGain.GetMaxPartGainValue()
} else {
attrPartV := MaxGain.GetMaxPartGainValue()
attrSubV := attrPartV.(tekstus.ListStrings)
splitV = attrSubV[0].Normalize()
}
//.........这里部分代码省略.........