In Finland, forest site types are used to assess the need of silvicultural operations and the growth potential of the forests and, therefore, provide important inventory information. This study introduces airborne laser scanner (ALS) data and the k-NN classifier data analysis technique applicable to the site quality assessment of mature forests. Both the echo height and the intensity value perc...

Many distance-based methods in machine learning are able to identify similar cases or prototypes from which decisions can be made. The explanation given is usually based on expressions such as ”because case a is similar to case b”. However, a more general or meaningful pattern, such as ”because case a has properties x and y (as b has)” is usually more difficult to find. Even in this case, the c...

Blogs are interactive and regularly updated websites which can be seen as diaries. These websites are composed by articles based on distinct topics. Thus, it is necessary to develop Information Retrieval approaches for this new web knowledge. The first important step of this process is the categorization of the articles. The paper above compares several methods using linguistic knowledge with k...

We examine the effectiveness of distance preserving transformations in privacy preserving data mining. These techniques are potentially very useful in that some important data mining algorithms can be efficiently applied to the transformed data and produce exactly the same results as if applied to the original data e.g. distance-based clustering, k-nearest neighbor classification. However, the ...

Non-deterministic matrices, a natural generalization of many-valued matrices, are semantic structures in which the value assigned to a complex formula may be chosen non-deterministically from a given set of options. We show that by combining non-deterministic matrices and distance-based considerations, one obtains a family of logics that are useful for reasoning with uncertainty. These logics a...

The authors present a new biometric classification procedure based on meanwave’s distances of electrocardiogram (ECG) heartbeats. The ECG data was collected from 63 subjects during two data-recording sessions separated by six months (Time Instance 1, T1, and Time Instance 2, T2). Two classification tests were performed with the goal of subject identification using a distance-based method with t...

This paper proposes a kNN model-based feature selection method aimed at improving the efficiency and effectiveness of the ReliefF method by: (1) using a kNN model as the starter selection, aimed at choosing a set of more meaningful representatives to replace the original data for feature selection; (2) integration of the Heterogeneous Value Difference Metric to handle heterogeneous applications...

This paper describes the combination of k-NN and SVM with LSI to improve their performance in single-label text categorization tasks, and the experiments performed with six datasets to show that both k-NN-LSI (the combination of k-NN with LSI) and SVM-LSI (the combination of SVM with LSI) outperform the original methods for a significant fraction of the datasets. Overall, both combinations pres...

Figure 1 gives the official results for the Hughes Trainable Text Skimmer used for MUC 3 (TTS-MUC3) . TTS is a largely statistical system, using a K-Nearest Neighbor classifie r with the output of a shallow parser as features. (See the System Summary section of thi s volume for a detailed description of TTS-MUC3). The performance, on a slot by slot basi s is, therefore, what one might expect: t...

This paper implements a simple vector space model relying on lexico-syntactic patterns to distinguish between the paradigmatic relations synonymy, antonymy and hypernymy. Our study is performed across word classes, and models the lexical relations between German nouns, verbs and adjectives. Applying nearest-centroid classification to the relation vectors, we achieve a precision of 59.80%, which...