Data Mining with Decision Trees: Theory and Applications by Lior Rokach

By Lior Rokach

Determination bushes became probably the most robust and renowned techniques in wisdom discovery and information mining; it's the technological know-how of exploring huge and complicated our bodies of knowledge as a way to realize necessary styles. determination tree studying maintains to adapt over the years. present tools are continuously being superior and new tools introduced.

This 2d variation is devoted solely to the sphere of selection timber in facts mining; to hide all elements of this significant method, in addition to more suitable or new tools and strategies constructed after the ebook of our first version. during this re-creation, all chapters were revised and new subject matters introduced in. New issues contain Cost-Sensitive energetic studying, studying with doubtful and Imbalanced information, utilizing choice bushes past class projects, privateness keeping selection Tree studying, classes discovered from Comparative reports, and studying determination bushes for large facts. A walk-through consultant to present open-source facts mining software program can be integrated during this variation.

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Target the mailing audience with the highest probability of positively responding to the marketing offer without exceeding the marketing budget. Another example deals with a security officer in an air terminal. Following September 11, the security officer needs to search all passengers August 18, 2014 19:12 Data Mining with Decision Trees (2nd Edition) - 9in x 6in b1856-ch04 page 38 Data Mining with Decision Trees 38 who may be carrying dangerous instruments (such as scissors, penknives and shaving blades).

12) The denominator stands for the total number of instances that are classified as positive in the entire dataset. Formally, it can be calculated as: n+ = |{< xi , yi >: yi = pos}|. 13) Lift Curve A popular method of evaluating probabilistic models is lift . After a ranked test set is divided into several portions (usually deciles), lift is calculated as follows [Coppock (2002)]: the ratio of really positive instances in a specific decile is divided by the average ratio of really positive instances in the population.

Note that these page 28 August 18, 2014 19:12 Data Mining with Decision Trees (2nd Edition) - 9in x 6in b1856-ch03 A Generic Algorithm for Top-Down Induction of Decision Trees page 29 29 TreeGrowing (S,A,y,SplitCriterion,StoppingCriterion) Where: S - Training Set A - Input Feature Set y - Target Feature SplitCriterion --- the method for evaluating a certain split StoppingCriterion --- the criteria to stop the growing process Create a new tree T with a single root node. IF StoppingCriterion(S) THEN Mark T as a leaf with the most common value of y in S as a label.

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