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I am attempting to do some evaluation of the relative rates of different algorithms in the C# and F# realms using WekaSharp and one of the algorithms I was interested in was Markov Chains. I know Weka has an HMM application but I have not been able to implement this into WekaSharp and was wondering if there was a way to modify the J48 Algorithm to suit this purpose. I know there is some similarity between J48 and first order Markov chains but am trying to determine what needs to be modified and if this is a reasonable thing to do. Here is the J48 as implemented in Yin Zhu's WekaSharp:

type J48() =
    static member DefaultPara =  "-C 0.25 -M 2"
    static member MakePara(?binarySplits, ?confidenceFactor, ?minNumObj, ?unpruned, ?useLaplace) =
        let binarySplitsStr = 
            let b = match binarySplits with
                    | Some (v) -> v
                    | None -> false
            if not b then "-B" else ""
        let confidenceFactorStr = 
            let c = match confidenceFactor with
                    | Some (v) -> v
                    | None -> 0.25 // default confi
            "-C " + c.ToString()
        let minNumObjStr = 
            let m = match minNumObj with
                    | Some (v) -> v
                    | None -> 2
            "-M " + m.ToString()
        let unprunedStr = 
            let u = match unpruned with
                    | Some (v) -> v
                    | None -> false
            if u then "-U" else ""
        let useLaplaceStr = 
            let u = match useLaplace with
                    | Some (v) -> v
                    | None -> false
            if u then "-A" else ""
        binarySplitsStr + " " + confidenceFactorStr + " " + minNumObjStr + " " + unprunedStr + " " + useLaplaceStr

Thank you very much.

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1 回答 1

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J48 只是C4.5 算法的一个实现，它通过考虑每个属性（维度）的熵并将具有最大熵的属性作为当前子树的根来学习决策树。该算法不需要强化。

我猜马尔可夫链是指用于强化学习的隐马尔可夫模型。

你应该看看HMMWeka。

一个相关的问题是： WEKA 工具包中隐马尔可夫模型的等价物是什么？

于 2014-03-20T16:32:09.753 回答