###### Grafting (**decision** **trees**)

A

**decision****tree**is a graphical model that is used as a support tool for**decision**process. Once the**decision****tree**is constructed ... Pruning allows cutting parts of**decision****trees**to give more clarity and Grafting adds nodes to the**decision****trees**to increase ...**Decision****Tree**Grafting R-**tree**implementation using branch-grafting method (R-**tree**implementation) Deep copy and persistence of ... One such**decision****tree**is as follows, Here the X-axis is represented as A and Y-axis as B. There are two cuts in the**decision**...###### Pruning (**decision** **trees**)

MDL based

**decision****tree**pruning**Decision****tree**pruning using backpropagation neural networks Fast, Bottom-Up**Decision****Tree**... One of the questions that arises in a**decision****tree**algorithm is the optimal size of the final**tree**. A**tree**that is too large ... Pruning is a technique in machine learning that reduces the size of**decision****trees**by removing sections of the**tree**that ... 269-272 Mansour, Y. (1997), "Pessimistic**decision****tree**pruning based on**tree**size", Proc. 14th International Conference on ...###### **Decision** **tree**

A

**decision****tree**is a**decision**support tool that uses a**tree**-like graph or model of**decisions**and their possible consequences, ... Among**decision**support tools,**decision****trees**(and influence diagrams) have several advantages.**Decision****trees**: Are simple to ...**Decision**cycle**Decision**list**Decision**table**Decision****tree**model of computation Design rationale DRAKON Markov chain Random ...**Decision****trees**can also be seen as generative models of induction rules from empirical data. An optimal**decision****tree**is then ...###### Alternating **decision** **tree**

An alternating

**decision****tree**(ADTree) is a machine learning method for classification. It generalizes**decision****trees**and has ... An alternating**decision****tree**consists of**decision**nodes and prediction nodes.**Decision**nodes specify a predicate condition. ... Figure 6 in the original paper demonstrates that ADTrees are typically as robust as boosted**decision****trees**and boosted**decision**... Original boosting algorithms typically used either**decision**stumps or**decision****trees**as weak hypotheses. As an example, ...###### Incremental **decision** **tree**

An incremental

**decision****tree**algorithm is an online machine learning algorithm that outputs a**decision****tree**. Many**decision****tree**... Post-Pruning Incremental**Decision****Trees**. Utgoff, P. E., Berkman, N. C., & Clouse, J. A. (1997)**Decision****tree**induction based on ... Incremental**decision****tree**methods allow an existing**tree**to be updated using only new individual data instances, without having ... ITI (1997) is an efficient method for incrementally inducing**decision****trees**. The same**tree**is produced for a dataset regardless ...###### **Decision** **tree** model

Linear

**decision****trees**, just like the simple**decision****trees**, make a branching**decision**based on a set of values as input. As ... The Las Vegas**decision**-**tree**complexity R 0 ( f ) {\displaystyle R_{0}(f)} measures the expected depth of a**decision****tree**that ... The quantum**decision****tree**complexity Q 2 ( f ) {\displaystyle Q_{2}(f)} is the depth of the lowest-depth quantum**decision****tree**... Algebraic**decision****trees**are a generalization of linear**decision****trees**to allow test functions to be polynomials of degree d. ...###### **Decision** **tree** learning

... is the construction of a

**decision****tree**from class-labeled training tuples. A**decision****tree**is a flow- ...**Decision****Trees**Tutorial using Microsoft Excel.**Decision****Trees**page at aitopics.org, a page with commented links.**Decision****tree**... a**decision****tree**can be used to visually and explicitly represent**decisions**and**decision**making. In data mining, a**decision****tree**... Deep**Decision****Tree**, Implementation Evolutionary Learning of**Decision****Trees**in C++ Java implementation of**Decision****Trees**based ...###### Information gain in **decision** **trees**

This biases the

**decision****tree**against considering attributes with a large number of distinct values. However, attributes with ... For example, suppose that one is building a**decision****tree**for some data describing the customers of a business. Information ... However, in the context of**decision****trees**, the term is sometimes used synonymously with mutual information, which is the ... but we do not want to include it in the**decision****tree**: deciding how to treat a customer based on their credit card number is ...###### Oracle Data Mining

ODM offers a choice of well-known machine learning approaches such as

**Decision****Trees**, Naive Bayes, Support vector machines, ... Support Vector Machine (SVM).**Decision****Trees**(DT). Anomaly detection. One-class Support Vector Machine (SVM). Regression ...###### ID3 algorithm

At runtime, this

**decision****tree**is used to classify new unseen test cases by working down the**decision****tree**using the values of ...**Decision****Tree**attribute for Root = A. For each possible value, vi, of A, Add a new**tree**branch below Root, corresponding to the ... In**decision****tree**learning, ID3 (Iterative Dichotomiser 3) is an algorithm invented by Ross Quinlan used to generate a**decision**... To avoid overfitting, smaller**decision****trees**should be preferred over larger ones. This algorithm usually produces small**trees**...###### Ross Quinlan

ID3 follows the principle of Occam's razor in attempting to create the smallest

**decision****tree**possible. He then expanded upon ... He has contributed extensively to the development of**decision****tree**algorithms, including inventing the canonical C4.5 and ID3 ... ISBN 1-55860-238-0. Quinlan, J. R. (1986). Induction of**decision****trees**. Machine Learning, 1(1):81-106. 2008. (with Qiang Yang, ... The advantages are several orders of magnitude faster, memory efficiency, smaller**decision****trees**, boosting (more accuracy), ...###### Recursive partitioning

See

**decision****tree**. As compared to regression analysis, which creates a formula that health care providers can use to calculate ... Recursive partitioning creates a**decision****tree**that strives to correctly classify members of the population by splitting it ... 1996). "Prospective validation of a**decision**rule for the use of radiography in acute knee injuries". JAMA. 275 (8): 611-5. doi ... Allows varying prioritizing of misclassifications in order to create a**decision**rule that has more sensitivity or specificity. ...###### Digital conversation

The script takes the form of a

**Decision**-**Tree**and is the backbone of the Digital Conversation. Each**Decision**-**Tree**defines two or ...**Decision**-**tree**logic >> Behavioural economics A Digital Conversation can be created for any scripted dialogue, thus it is suited ...###### Photovoltaic power station

"Screening Sites for Solar PV Potential" (PDF). Solar

**Decision****Tree**. US Environmental Protection Agency. Retrieved 5 March 2013 ...###### Deep learning

... by adopting large output layers of the DNN based on context-dependent HMM states constructed by

**decision****trees**. Advances in ... "Mastering the game of Go with deep neural networks and**tree**search". Nature. 529 (7587): 484-489. Bibcode:2016Natur.529..484S. ...###### Uplift modelling

Typically this would use

**decision****trees**or regression analysis. This model would only use the treated customers to build the ... Together with Szymon Jaroszewicz he adapted information theory to build multi class uplift**decision****trees**and published the ... Rzepakowski, Piotr; Jaroszewicz, Szymon (2010). "**Decision****trees**for uplift modeling". In Proceedings of the 10th IEEE ... Rzepakowski, Piotr; Jaroszewicz, Szymon (2011). "**Decision****trees**for uplift modeling with single and multiple treatments". ...###### Financial economics

See for example: Magee, John F. (1964). "

**Decision****Trees**for**Decision**Making". Harvard Business Review. July 1964: 795-816. ... More traditionally,**decision****trees**-which are complementary-have been used to evaluate projects, by incorporating in the ... Aswath Damodaran (2007). "Probabilistic Approaches: Scenario Analysis,**Decision****Trees**and Simulations". In Strategic Risk ... Edgeworth binomial**trees**allow for a specified (i.e. non-Gaussian) skew and kurtosis in the spot price; priced here, options ...###### **Tree** diagram (probability theory)

**Decision**

**tree**"

**Tree**Diagrams". BBC GCSE Bitesize. BBC. p. 1,3. Retrieved 25 October 2013. Charles Henry Brase, Corrinne ... In probability theory, a

**tree**diagram may be used to represent a probability space.

**Tree**diagrams may represent a series of ... 205-208 (online copy at Google)

**tree**diagrams - explanations and examples

**tree**diagrams - examples and applications. ...

###### Cascading classifiers

Minguillón, J. (2002). On Cascading Small

**Decision****Trees**(PhD thesis). Universitat Autònoma de Barcelona. Zhao, H.; Ram, S. ( ... a**decision****tree**would be: feature 1 negative feature 2 negative feature 3 negative -> class2 feature 3 positive -> class1 ... "Constrained Cascade Generalization of**Decision****Trees**". IEEE Transactions on Knowledge and Data Engineering. 16 (6): 727-739. ... This leads to a**tree**with too few samples on the leaves. A two-stage algorithm can effectively merge these two cases by giving ...###### BrownBoost

Dietterich, T. G., (2000). An experimental comparison of three methods for constructing ensembles of

**decision****trees**: Bagging, ...###### Mediation

"International Mediation Institute

**Decision****Tree**". Retrieved 1 March 2012. Simkin, W. E., (1971); Mediation and the Dynamics of ... Boulle 2005 The International Mediation Institute has a**decision****tree**on its website, which is designed to help the parties to ... Arbiters'**decisions**are typically final and appeals are rarely successful even if the**decision**appears to one party to be ... making their own**decisions**. Those**decisions**can include settlement agreements or not. Transformative mediation practice is ...###### Vulnerability index

**Decision**

**trees**can evaluate alternative policy options. Much of the original research has been evaluated by Lino Briguglio and ...

###### Rule induction

"Generating production rules from

**decision****trees**" (PDF). In McDermott, John. Proceedings of the Tenth International Joint ... Some major rule induction paradigms are: Association rule learning algorithms (e.g., Aggrawal)**Decision**rule algorithms (e.g., ...###### Riverview Hospital (Coquitlam)

As early as 1967 a

**decision**had been made to downsize Riverview Hospital. The**decision**was first brought up officially on paper ... Do you think that paint grows on**trees**? Have you priced a can of pain recently? Do you know the hourly rate for a journeyman ... By 1990 the**decision**had officially been made to reduce Riverview to a 358-bed facility with the supposed intention of opening ... The report "emphasizes that a full assessment of patients'**decision**-making abilities and personal support network is necessary ...###### Multiclass classification

**Decision**

**trees**are a powerful classification technique. The

**tree**tries to infer a split of the training data based on the ... Several algorithms have been developed based on neural networks,

**decision**

**trees**, k-nearest neighbors, naive Bayes, support ... This strategy requires the base classifiers to produce a real-valued confidence score for its

**decision**, rather than just a ... Hierarchical classification tackles the multi-class classification problem by dividing the output space i.e. into a

**tree**. Each ...