I argue that the numbering system of Tractatus lets us see how it was constructed, in two closely related senses term. First, tells a great deal about genesis book, for used to assemble and rearrange series drafts, as recorded MS 104. Second, helps understand structure published cryptically summarized opening footnote. also discuss an unpublished letter from Anscombe von Wright 1948 which conta...

A tree-structured classifier is a decision tree for predicting a class variable from one or more predictor variables. THAID [15, 7] was the first such algorithm. This article focuses on the CART R © [2], C4.5 [17], and GUIDE [12] methods. The algorithms are briefly reviewed and their similarities and differences compared on a real data set and by simulation. In a typical classification problem,...

We propose adaptive testing as a general mechanism for extracting information about stimuli from spike trains. Each test or question corresponds to choosing a neuron and a time interval and checking for a given number of spikes. No assumptions are made about the distribution of spikes or any other aspect of neural encoding. The chosen questions are those which most reduce the uncertainty about ...

Classification and regression trees are becoming increasingly popular for partitioning data and identifying local structure in small and large datasets. Classification trees include those models in which the dependent variable (the predicted variable) is categorical. Regression trees include those in which it is continuous. This paper discusses pitfalls in the use of these methods and highlight...

A tree-structured classifier is a decision tree for predicting a class variable from one or more predictor variables. THAID [15, 7] was the first such algorithm. This article focuses on the CART R © [2], C4.5 [17], and GUIDE [12] methods. The algorithms are briefly reviewed and their similarities and differences compared on a real data set and by simulation. In a typical classification problem,...

Many kinds of variable-sized data we would like to model contain an internal hierarchical structure in the form of a tree, including source code, formal logical statements, and natural language sentences with parse trees. For such data it is natural to consider a model with matching computational structure. In this work, we introduce a variational autoencoder-based generative model for tree-str...

We present Tree, a new approach to structural classification. This integrated approach induces decision trees that test for pattern occurrence in the inner nodes. It combines state-of-the-art tree mining with sophisticated pruning techniques to find the most discriminative pattern in each node. In contrast to existing methods, Tree uses no heuristics and only a single, statistically well founde...

This paper introduces the algorithm TREE DIAG for computing minimal diagnoses for tree structured systems. Diagnoses are computed by descending into the tree, enumerating the input combinations that might be reponsible for a given incorrect observation, and combining the diagnoses for the subtrees generating these inputs into diagnoses for the whole system. We prove soundness and correctness of...