Pruning methods

Mingers, J., 1989. An Empirical Comparison of Pruning Methods for Decision Tree Induction. Machine Learning, 4, 221. 

Leafing Vine Growth Pruning Method Harvest Period Average Cluster Productivity Weight (lb) (tons/acre) ... 

Allen MS, Tassie E, Lacey MJ, Brown WV, Harris RLN(1990b) Influence of pruning methods on methoxypyrazine flavour components of Cabernet Sauvignon grapes. In Williams PJ, Davidson D, Lee TH (eds) Proceedings of the seventh Australian wine industry technical conference, 13-17 Aug 1989. Winetitles, Adelaide, pp 247... 

Nowadays, as the rapid development of data collection techniques, more and more data are collected, and wrapper methods cannot meet the need of rapid data processing. Then, a number of input pruning methods using SVM have been developed. Guyon and his co-workers proposed to use optimal brain damage as the feature evaluation method and combined it with recursive feature elimination to perform gene selection [64],... 

Grassberger P 1997 Pruned-enriched Rosenbluth method simulations of theta polymers of chain length up to 1,000,000 Phys. Rev. E 56 3682... 

The main difference between the G2 models is tlie way in which tlie electron correlation beyond MP2 is estimated. The G2 method itself performs a series of MP4 and QCISD(T) calculations, G2(MP2) only does a single QCISD(T) calculation with tlie 6-311G(d,p) basis, while G2(MP2, SVP) (SVP stands for Split Valence Polarization) reduces the basis set to only 6-31 G(d). An even more pruned version, G2(MP2,SV), uses the unpolarized 6-31 G basis for the QCISD(T) part, which increases the Mean Absolute Deviation (MAD) to 2.1 kcal/mol. That it is possible to achieve such good performance with tliis small a basis set for QCISD(T) partly reflects the importance of the large basis MP2 calculation and partly the absorption of errors in the empirical correction. 

The selection of the descriptors can happen in a forward or backward manner. A model created using the forward method starts with one descriptor followed by the addition of descriptors to the model until the model meets the specifications of the user. Models created in the backward method start with all the possible descriptors descriptors are taken away as they are deemed unnecessary. It is safe to assume that most QSAR models are created using the forward method due to the sheer number of descriptors and the desire for only a few in the model. Models can be pruned using the backward method specifically, once the model is created, the user wants to reduce the number of descriptors yet keep the same level of validity for the model. 

Objective Find common feature configurations amongst a set of active molecules. Algorithm HipHop uses a pruned exhaustive search method. Starting with simple two-feature pharmacophores, the program tries to add one extra common feature at a time until no larger common pharmacophore configuration exists [10]. Combinations that cannot be completed to reach a minimum number of features are not further explored. 

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