In machine learning, decision trees are employed extensively in solving classification problems. In order to design a decision tree classifier two main phases are employed. The first phase is to grow the tree using a set of data, called training data, quite often to its maximum size. The second phase is to prune the tree. The pruning phase produces a smaller tree with better generalization (sma...

M5 is a method developed by Quinlan [10] for inducing trees of linear regression models (model trees). The paper addresses the flexibility and optimality in M5 model tree by proposing two new algorithms, namely M5flex and M5opt. M5flex algorithm brings in domain knowledge by enabling the user to choose split attributes and split values for important nodes in a model tree so that the resulting m...

The CN2 algorithm induces an ordered list of classiication rules from examples using entropy as its search heuristic. In this short paper, we describe two improvements to this algorithm. Firstly, we present the use of the Laplacian error estimate as an alternative evaluation function and secondly, we show how unordered as well as ordered rules can be generated. We experimentally demonstrate sig...

In this paper we explore the degree to which patents are representative of the magnitude, direction, and impact of the knowledge spilling out of the university by focusing on MIT, and in particular on the departments of Mechanical and Electrical Engineering. Drawing on both qualitative and quantitative data, we show that patenting is a minority activity: a majority of the faculty in our sample ...

In knowledge discovery from databases, we emphasize the need for learning from huge, incomplete and imperfect data sets (Piatetsky-Shapiro and Frawley, 1991). To handle noise in the problem domain, existing learning systems avoid overfitting the imperfect training examples by excluding insignificant patterns. The problem is that these systems use a limiting attribute-value language for represen...

We present an apparatus that allows independent stimulation of rods and short (S)-, middle (M)-, and long (L)-wavelength-sensitive cones. Previously presented devices allow rod and cone stimulation independently, but only for a spatially invariant stimulus design (Pokorny, Smithson, & Quinlan, 2004; Sun, Pokorny, & Smith, 2001b). We overcame this limitation by using two spectrally filtered proj...

Montero, S., Blanco, A., Virto, M. D., Landeta, L. C., Agud, I., Solozabel, R., Lascaray, J. M., De Renobles, M., Llama, M. J. and Serra, J. L. (1993) Enzyme Microb. Technol. 15,239-247 Huang, F.-C. and Ju, Y.-H. (1994) Biotechnol. Tech. 8,827-830 AIChE J. 35, 1551-1554 21 Bailie, P. M., McNerlan, S. E., Robinson, E. and Murphy, W. R. (1995) Trans. IChemE. 73, 71-76 22 Wehtje, E., Adlercreutz, ...

The submitters discuss an approach to measure the unpredictability of a pseudo-randomly generated key stream. They propose to use machine learning techniques: frames of a xed length from the bit stream together with the bit immediately following the frame are used as learning data for a classi cation algorithm. The idea is to assign the frames to two classes, namely the frames which are followe...

Using Mennin, Heimberg, Turk, and Fresco's [Emotion regulation deficits as a key feature of generalized anxiety disorder: Testing a theoretical model, submitted for publication] conceptualization of generalized anxiety disorder (GAD) as a syndrome involving emotion dysregulation and an overuse of cognitive control strategies, this study sought to differentiate individuals with GAD from controls...

There are several di erent ways data mining the automatic induction of knowledge from data can be applied to the problem of natural language processing In the past data mining techniques have mainly been used in linguistic engineering applications to solve knowledge acquisition bottlenecks In this paper we show that they can also assist in linguistic theory formation by providing a new tool for...