Grapevines can be modified by various trellising and pruning methods so they may be successfully mechanized. There are six conditions that must be optimized to successfully mechanize a vineyard. A properly trained vine allows efficient operations with out excessive damage to the vines or reduction of fruit yield and/ or quality. Shoot positioning can be accomplished efficiently with machines wh...

In this Thesis we study issues related to learning small tree and graph formed classifiers. First, we study reduced error pruning of decision trees and branching programs. We analyze the behavior of a reduced error pruning algorithm for decision trees under various probabilistic assumptions on the pruning data. As a result we get, e.g., new upper bounds for the probability of replacing a tree t...

Standard techniques for improved generalisation from neural networks include weight decay and pruning. Weight decay has a Bayesian interpretation with the decay function corresponding to a prior over weights. The method of transformation groups and maximum entropy indicates a Laplace rather than a Gaussian prior. After training, the weights then arrange themselves into two classes: (1) those wi...

Many techniques for model selection in the field of neural networks correspond to well established statistical methods. The method of 'stopped training', on the other hand, in which an oversized network is trained until the error on a further validation set of examples deteriorates, then training is stopped, is a true innovation, since model selection doesn't require convergence of the training...

In the last few years, the power and simplicity of classification trees as acoustic modeling tools have gained them much popularity. In [1], we studied ‘‘tree units’’, which cluster parameters at the HMM level. Building on this earlier work, we examine some new variants of Young et al’s ‘‘tree states’’, which cluster parameters at the state level [2]. We have experimented with: 1. Making unitar...

training is considered an important element in the organization, as it heavily influences people to learn how to be more effective at work by modifying knowledge, skills or attitudes through the learning experience to achieve a successful performance. likewise, training is a long term allegiance to all employees because they have to learn new skills and knowledge which become a turning point fo...

A major drawback associated with the use of artificial neural networks for data mining is their lack of explanation capability. While they can achieve a high predictive accuracy rate, the knowledge captured is not transparent and cannot be verified by domain experts. In this paper, Artificial Neural Network Tree (ANNT), i.e. ANN training preceded by Decision Tree rules extraction method is pres...

In this letter, we comment on "Pruning Error Minimization in Least Squares Support Vector Machines" by B. J. de Kruif and T. J. A. de Vries. The original paper proposes a way of pruning training examples for least squares support vector machines (LS SVM) using no regularization (-gamma = infinity). This causes a problem as the derivation involves inverting a matrix that is often singular. We di...