A Fast Modified Constructive Covering Algorithm for Multiclass Classification Problem in Data Miningdoi:10.5120/443-676Vikas ShrivastavaAruna TiwariRajan MalhotraFoundation of Computer Science FCS
In the online FDD process, the monitoring data are classified by the trained multi-class classifier. The classifier can tell which class the data belong to. The multiclass classification-based methods can also be further classified into two subcategories, i.e. support vector machine-based and ...
Urszula Chajewska, Rich Caruana The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’19)|August 2019 Generalized additive models (GAMs) are favored in many regression and binary classification problems because they are able to fit complex, nonlinear functions whil...
In this problem, the goal is to train a classification model that predicts each class for new (test) data. “Logistic regression” is used as a multiclass classifier. Other classifiers will be considered for this problem in Section Grid search and model selection. Similar to previous problems,...
Attribute selectionClassificationMulti-relational data miningMultivalued attributesRelevance measuresAn important step in the knowledge discovery in databases (KDD) process is the attribute selection procedure, which aims at choosing a subset of attributes that can represent the important information...
www.nature.com/scientificreports OPEN Classification performance assessment for imbalanced multiclass data Jesús S. Aguilar‑Ruiz 1,3* & Marcin Michalak 2,3 The evaluation of diagnostic systems is pivotal for ensuring the deployment of high-quality solutions, especially given the ...
Decision trees have been widely used in data mining and machine learning as a comprehensible knowledge representation. Originally the method to construct decision tree follows greedy approach which results in local tree and classification rules. Ant Colony Optimization (ACO) is a meta- heuristic approac...
The high dimensionality of microarray datasets endows the task of multiclass tissue classification with various difficulties--the main challenge being the ... Chiahuey Ooi,M Chetty,Shyhwei Teng - 《Data Mining & Knowledge Discovery》 被引量: 35发表: 2007年 The role of feature redundancy in tumo...
classification, i.e., marriage, birthday, and traveling, etc., to anticipate products and services to facilitate the people [40]. The data about life events exist in a very small amount. Linear regression, Naïve Bayes, and nearest neighbor algorithms were evaluated on the original dataset ...
Classification techniques are becoming more popular in the fields of medical, biostatistics, bioinformatics, agriculture, business etc. as machine learning applications. Machine learning is a subfield of artificial intelligence that enables computers to understand from existing data and estimate the existence...