Instance Selection to Improve Gamma Classifier
نویسندگان
چکیده
منابع مشابه
Instance Selection to Improve Gamma Classifier
Pre-processing the dataset is an important stage in the Knowledge Discovery in Datasets (KDD) process. Filtering noise through instance selection is a necessary task. With this, the risk to use misclassified and non-representative instances to train supervised classifiers is reduced. This study aims at improving the performance of the Gamma associative classifier, by introducing a novel similar...
متن کاملInstance Selection in the Performance of Gamma Associative Classifier
The Gamma associative classifier is among the most used classifiers of the alpha-beta associative approach. It had been used successfully to solve many Pattern Recognition tasks, including environmental applications. However, as most classifiers, Gamma suffers with the presence of noisy or mislabeled instances in the training sets. This paper evaluates the impact of using instance selection tec...
متن کاملImproving Cascade Classifier Precision by Instance Selection and Outlier Generation
Beside the curse of dimensionality and imbalanced classes, unfavorable data distributions can hamper classification accuracy. This is particularly problematic with increasing dimensionality of the classification task. A classifier that can handle high-dimensional and imbalanced data sets is the cascade classification method for time series. The cascade classifier can compound unfavorable data d...
متن کاملInstance Selection for Classifier Performance Estimation in Meta Learning
Building an accurate prediction model is challenging and requires appropriate model selection. This process is very time consuming but can be accelerated with meta-learning–automatic model recommendation by estimating the performances of given prediction models without training them. Meta-learning utilizes metadata extracted from the dataset to effectively estimate the accuracy of the model in ...
متن کاملInstance Selection
The amounts of data become increasingly large in recent years as the capacity of digital data storage worldwide has significantly increased. As the size of data grows, the demand for data reduction increases for effective data mining. Instance selection is one of the effective means to data reduction. This article introduces basic concepts of instance selection, its context, necessity and funct...
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: Polibits
سال: 2016
ISSN: 2395-8618,1870-9044
DOI: 10.17562/pb-54-9