A time series forest for classification and feature extraction
نویسندگان
چکیده
منابع مشابه
A Time Series Forest for Classification and Feature Extraction
A tree-ensemble method, referred to as time series forest (TSF), is proposed for time series classification. TSF employs a combination of entropy gain and a distance measure, referred to as the Entrance (entropy and distance) gain, for evaluating the splits. Experimental studies show that the Entrance gain improves the accuracy of TSF. TSF randomly samples features at each tree node and has com...
متن کاملFeature Extraction over Multiple Representations for Time Series Classification
We suggest a simple yet effective and parameter-free feature construction process for time series classification. Our process is decomposed in three steps: (i) we transform original data into several simple representations; (ii) on each representation, we apply a coclustering method; (iii) we use coclustering results to build new features for time series. It results in a new transactional (i.e....
متن کاملGrammar-guided Feature Extraction for Time Series Classification
We present a flexible, general-purpose technique for generating time series classifiers. These classifiers are two-stage algorithms; each consists of a set of feature extraction programs, used for transforming the time series into a vector of descriptive scalar features, and a back-end classifier (such as a support vector machine) which uses these features to predict a label. We use grammars to...
متن کاملA Real-Time Electroencephalography Classification in Emotion Assessment Based on Synthetic Statistical-Frequency Feature Extraction and Feature Selection
Purpose: To assess three main emotions (happy, sad and calm) by various classifiers, using appropriate feature extraction and feature selection. Materials and Methods: In this study a combination of Power Spectral Density and a series of statistical features are proposed as statistical-frequency features. Next, a feature selection method from pattern recognition (PR) Tools is presented to e...
متن کاملFeature eXtraction from sparse time series data
We present a computational methodology for qualitative analysis of sparse and noisy time series. Information about the changes of the signal level within a time series and the number of distinguishable signal levels is extracted and condensed into a pattern string. The qualitative analysis of a time series can be done at several levels of detail to generate pattern strings that encode the seque...
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: Information Sciences
سال: 2013
ISSN: 0020-0255
DOI: 10.1016/j.ins.2013.02.030