Information entropy for ordinal classification
نویسندگان
چکیده
منابع مشابه
Ordinal Patterns, Entropy, and EEG
In this paper we illustrate the potential of ordinal-patterns-based methods for analysis of real-world data and, especially, of electroencephalogram (EEG) data. We apply already known (empirical permutation entropy, ordinal pattern distributions) and new (empirical conditional entropy of ordinal patterns, robust to noise empirical permutation entropy) methods for measuring complexity, segmentat...
متن کاملLocal Ordinal Classification
Given ordered classes, one is not only concerned to maximize the classification accuracy, but also to minimize the distances between the actual and the predicted classes. This paper offers an organized study on the various methodologies that have tried to handle this problem and presents an experimental study of these methodologies with the proposed local ordinal technique, which locally conver...
متن کاملClassification of Ordinal Data
Predictive learning has traditionally been a standard inductive learning, where different subproblem formulations have been identified. One of the most representative is classification, consisting on the estimation of a mapping from the feature space into a finite class space. Depending on the cardinality of the finite class space we are left with binary or multiclass classification problems. F...
متن کاملoAdaBoost - An AdaBoost Variant for Ordinal Classification
Ordinal data classification (ODC) has a wide range of applications in areas where human evaluation plays an important role, ranging from psychology and medicine to information retrieval. In ODC the output variable has a natural order; however, there is not a precise notion of the distance between classes. The Data Replication Method was proposed as tool for solving the ODC problem using a singl...
متن کاملSelecting Features for Ordinal Text Classification
We present four new feature selection methods for ordinal regression and test them against four different baselines on two large datasets of product reviews.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Science China Information Sciences
سال: 2010
ISSN: 1674-733X,1869-1919
DOI: 10.1007/s11432-010-3117-7