本文整理汇总了Golang中github.com/sjwhitworth/golearn/base.Instances.GetClassDistribution方法的典型用法代码示例。如果您正苦于以下问题：Golang Instances.GetClassDistribution方法的具体用法？Golang Instances.GetClassDistribution怎么用？Golang Instances.GetClassDistribution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/sjwhitworth/golearn/base.Instances的用法示例。
在下文中一共展示了Instances.GetClassDistribution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: GetSplitAttributeFromSelection
// GetSplitAttributeFromSelection returns the class Attribute which maximises
// the information gain amongst consideredAttributes
//
// IMPORTANT: passing a zero-length consideredAttributes parameter will panic()
func (r *InformationGainRuleGenerator) GetSplitAttributeFromSelection(consideredAttributes []int, f *base.Instances) base.Attribute {
// Next step is to compute the information gain at this node
// for each randomly chosen attribute, and pick the one
// which maximises it
maxGain := math.Inf(-1)
selectedAttribute := -1
// Compute the base entropy
classDist := f.GetClassDistribution()
baseEntropy := getBaseEntropy(classDist)
// Compute the information gain for each attribute
for _, s := range consideredAttributes {
proposedClassDist := f.GetClassDistributionAfterSplit(f.GetAttr(s))
localEntropy := getSplitEntropy(proposedClassDist)
informationGain := baseEntropy - localEntropy
if informationGain > maxGain {
maxGain = informationGain
selectedAttribute = s
}
}
// Pick the one which maximises IG
return f.GetAttr(selectedAttribute)
}