ShengYg's Blog

水塘抽样算法 -- Reservoir Sampling。在序列流中取k个数，确保取出某个数据的概率为:k/n

用Manacher算法解决最长回文子串问题，时间复杂度为O(n)

字符串匹配算法 -- KMP算法

Several common types of ensemble learning

XGBoost (eXtreme Gradient Boosting) is an advanced implementation of gradient boosting algorithm. If things don’t go your way in predictive modeling, use XGboost. XGBoost algorithm has become the ultimate weapon of many data scientist. It’s a highly sophisticated algorithm, powerful enough to deal with all sorts of irregularities of data.

Boosting is a sequential technique which works on the principle of ensemble. It combines a set of weak learners and delivers improved prediction accuracy. At any instant t, the model outcomes are weighed based on the outcomes of previous instant t-1. The outcomes predicted correctly are given a lower weight and the ones miss-classified are weighted higher.

example

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