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In decision tree learning, information gain ratio is a ratio of information gain to the intrinsic information. It was proposed by Ross Quinlan, [1] to reduce a bias towards multi-valued attributes by taking the number and size of branches into account when choosing an attribute. [2] Information gain is also known as mutual information. [3]
In a data-aided approach, the channel estimation is based on some known data, which is known both at the transmitter and at the receiver, such as training sequences or pilot data. [8] In a blind approach, the estimation is based only on the received data, without any known transmitted sequence. The tradeoff is the accuracy versus the overhead.
Although information gain is usually a good measure for deciding the relevance of an attribute, it is not perfect. A notable problem occurs when information gain is applied to attributes that can take on a large number of distinct values. For example, suppose that one is building a decision tree for some data describing the customers of a business.
ID3 is harder to use on continuous data than on factored data (factored data has a discrete number of possible values, thus reducing the possible branch points). If the values of any given attribute are continuous , then there are many more places to split the data on this attribute, and searching for the best value to split by can be time ...
Download QR code; Print/export ... , depends on the random channel gain | | , which is unknown to the ... If the transmitter encodes data at rate ...
Discounted cumulative gain (DCG) is a measure of ranking quality in information retrieval. It is often normalized so that it is comparable across queries, giving Normalized DCG (nDCG or NDCG) . NDCG is often used to measure effectiveness of search engine algorithms and related applications.
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Luchman, J.N.; CHAIDFOREST: Stata module to conduct random forest ensemble classification based on chi-square automated interaction detection (CHAID) as base learner, Available for free download, or type within Stata: ssc install chaidforest. IBM SPSS Decision Trees grows exhaustive CHAID trees as well as a few other types of trees such as CART.