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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]
Information gain is the basic criterion to decide whether a feature should be used to split a node or not. The feature with the optimal split i.e., the highest value of information gain at a node of a decision tree is used as the feature for splitting the node.
The information gain in decision trees (,), which is equal to the difference between the entropy of and the conditional entropy of given , quantifies the expected information, or the reduction in entropy, from additionally knowing the value of an attribute . The information gain is used to identify which attributes of the dataset provide the ...
J&J's fourth-quarter sales stood at $22.52 billion, up 5.3% from a year ago and above analysts' expectations of $22.42 billion, according to LSEG data. On an adjusted basis, the company earned $2. ...
In a complaint filed in Washington, D.C. federal court, the SEC said Musk violated federal securities law by waiting 11 days too long to disclose his initial purchase of 5% of Twitter's common shares.
A California federal judge on Tuesday expressed doubt over Elon Musk's "irreparable harm" claims in his lawsuit against Sam Altman.
"Information wants to be free" is an expression that means either that all people should be able to access information freely, or that information (formulated as an actor) naturally strives to become as freely available among people as possible. It is often used by technology activists to criticize laws that limit transparency and general ...
Wall Street analysts expect gold's rally to keep going in 2025 after the precious metal saw its biggest annual jump in 14 years. On Thursday, gold futures jumped more than 1% to hover above $2,670 ...