Improving feature selection algorithms using normalised feature histograms
نویسندگان
چکیده
منابع مشابه
Improving feature selection algorithms using normalised feature histograms
The proposed feature selection method builds a histogram of the most stable features from random subsets of training set and ranks the features based on a classifier based cross validation. This approach reduces the instability of features obtained by conventional feature selection methods that occur with variation in training data and selection criteria. Classification results on 4 microarray ...
متن کاملImproving of Feature Selection in Speech Emotion Recognition Based-on Hybrid Evolutionary Algorithms
One of the important issues in speech emotion recognizing is selecting of appropriate feature sets in order to improve the detection rate and classification accuracy. In last studies researchers tried to select the appropriate features for classification by using the selecting and reducing the space of features methods, such as the Fisher and PCA. In this research, a hybrid evolutionary algorit...
متن کاملImproving Human Gait Recognition Using Feature Selection
Human gait, a biometric aimed to recognize individuals by the way they walk has recently come to play an increasingly important role in visual surveillance applications. Most of the existing approaches in this area, however, have mostly been evaluated without explicitly considering the most relevant gait features, which might have compromised the performance. In this paper, we have investigated...
متن کاملRobust Feature Selection Algorithms
Selecting a set of features which is optimal for a given task is a problem which plays an important role in a wide variety of contexts including pattern recognition, adaptive control, and machine learning. Our experience with traditional feature selection algorithms in the domain of machine learning lead to an appreciation for their computational efficiency and a concern for their brittleness. ...
متن کاملNovel Randomized Feature Selection Algorithms
Feature selection is the problem of identifying a subset of the most relevant features in the context of model construction. This problem has been well studied and plays a vital role in machine learning. In this paper we present three randomized algorithms for feature selection. They are generic in nature and can be applied for any learning algorithm. Proposed algorithms can be thought of as a ...
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: Electronics Letters
سال: 2011
ISSN: 0013-5194
DOI: 10.1049/el.2010.3672